Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAIL OFFICE ACTIONS
The United States Patent & Trademark Office appreciates the response filed for the current application that is submitted on 07/07/2026. The United States Patent & Trademark Office reviewed the following documents submitted and has made the following comments below.
Priority
Applicant claims the benefit of National Stage Application PCT/US2023/061473, filed on 01/27/2023. Claims 1-20 have been afforded the benefit of this filing date.
Amendment
Applicant submitted amendments on 07/07/2026. The Examiner acknowledges the amendment and has reviewed the claims accordingly.
Drawings
The drawings were received on 03/20/2024. The drawings are acceptable.
Information Disclosure Statement
The Information Disclosure Statement filed on 03/20/2024 has been considered by the examiner (see attached PTO-1449 or PTO/SB/08A and 08B forms.). The Examiner has considered all the items on the IDS.
Status of Claims
Claims 1-20 are pending
Claims 21-40 are cancelled
Claims 1-7, 9-12, and 14-20 are rejected.
Applicant Arguments:
Regarding Argument 1, see remarks (page 8), filed 07/07/2026, Applicant/s state/s “the specification stands as objected to due to informalities. The specification is amended taking into consideration the Examiner’s comments. Reconsideration and withdrawal of the objection is respectfully requested.”
Regarding Argument 2, see remarks (page 8), filed 07/07/2026, Applicant/s state/s “Claim 12 stands rejected under 35 U.S.C. 112 as allegedly being indefinite. The claims are amended taking into consideration the Examiner’s comments. Reconsideration and withdrawal of the rejection to claim 12 under 35 U.S.C. 112 is respectfully requested.”
Regarding Argument 3, see remarks (page 9), filed 07/07/2026, Applicant/s state/s “These (35 U.S.C. 103) rejections are respectfully traversed for the reasons detailed below: As agreed during the Examiner interview, the cited references fail to disclose, or render obvious, the subject matter of currently-pending claims 1-7, 9-12, and 14-20. Reconsideration and withdrawal of the rejection to claims 1-7, 9-12, and 14-20 under 35 U.S.C. 103(a) is respectfully requested.”
Examiner’s Responses:
In response to Argument 1, see remarks (page 8), filed 07/07/2026, with respect to the objection(s) of the specification have been fully considered and are persuasive. Therefore, the objection(s) to the specification has/have been withdrawn.
In response to Argument 2, see remarks (page 8), filed 07/07/2026, with respect to the rejection(s) of claim(s) 12 under 35 U.S.C. 112 have been fully considered and are persuasive. Therefore, the rejection(s) of claim(s) 12 under 35 U.S.C 112 has been withdrawn.
In response to Argument 3, see remarks (page 9), filed 07/07/2026, with respect to the rejection(s) of claim(s) 1-7, 9-12, and 14-20 under 35 U.S.C. 103(a) have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made for Claims 1 and 10 in view of Donovan et al. (U.S. Patent Pub. No. 20120213435 A1, hereafter referred to as Donovan) in view of Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov).
A new ground(s) of rejection is also made for Claims 2-6 in view of Donovan in view of
Filippov in further view of Goswami et al. (U.S. Patent Pub. No. 2023/0336745 A1, hereafter referred to as Goswami).
A new ground(s) of rejection is also made for Claim 7 in view of Donovan in view of Filippov in further view of Goswami in further view of Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim).
A new ground(s) of rejection is also made for Claim 9 in view of Donovan in view of Filippov in further view of Kim in further view of Astle (U.S. Patent No. 5,590,064, hereafter referred to as Astle).
A new ground(s) of rejection is also made for Claim 11 in view of Donovan in view of Filippov in further view of Kim.
A new ground(s) of rejection is also made for Claims 12 and 15-20 in view of Donovan in view of Werness et al. (U.S. Patent Pub No. 2013/0022265 A1, hereafter referred to as Werness) in further view of Filippov.
A new ground(s) of rejection is also made for Claim 14 in view of Donovan in view of Werness in further view of Filippov in further view of Astle.
Regarding amended Claim 1, the Examiner finds that Filippov teaches the amended claim language, “generating, by the pre-processor, base values and delta values based on an image”. Filippov teaches a mode selection unit (260) comprises partitioning unit (262), inter-prediction unit (244) and intra-prediction unit (254), and is configured to receive/obtain original picture data, e.g., an original block (203), and reconstructed picture data from a buffer. The reconstructed picture data is used as reference picture data for prediction, e.g., inter-prediction or intra-prediction, to obtain a prediction block (265) or “predictor” (265) (Paragraphs [0119-120]). The Examiner interprets the “prediction block” (265) values (pixel values) are base values. Further, under BRI, the Examiner interprets the prediction block is generated by a “pre-processor” since the mode selection unit (260) which processes the picture block/reconstructed picture data to generate the prediction block (265, Fig. 2) does the generating prior to the encoding performed by the entropy encoding unit (270, Fig. 2). Filippov also teaches generating delta values based on an image. Specifically, Filippov teaches a residual calculation unit (204) may be configured to calculate a residual block (205) or “residual” based on picture block (203) and a prediction block (265) by subtracting sample (pixel) values of the prediction block (265) from sample (pixel) values of the picture block (203), sample by sample (pixel by pixel) to obtain the residual block (205) in the sample domain (Paragraph [0106]). Additionally, the Examiner interprets the residual calculation unit (204) to be a “pre-processor” since it calculates the residual block (205) prior to the image encoding by the entropy encoding unit (270, Fig. 2). Next, the Examiner finds that Filippov teaches the amended claim language, “generating, by the pre-processor, weighted delta values based on the delta values.” Filippov teaches a transform processing unit (206) may be configured to apply a transform, such as a discrete cosine transform (DCT) or a discrete sine transform (DST), on the sample (pixel) values of the residual block (205) to obtain transform coefficients (207) in a transform domain. The transform coefficients (207) may be referred to as transform residual coefficients and represent the residual block (205) in the transform domain (Paragraph [0107]). Additional scaling factors are applied to the residual block as part of the transform process. Scaling factors are typically chosen based on certain constraints (Paragraph [0108]). The Examiner interprets scaling factors applied to the residuals to be the “weighted delta values”. Further, the Examiner interprets they are generated by a “pre-processor” since the transform processing unit (206)/quantization unit (208) perform processing prior to the encoding of the image data via the entropy encoding unit (270) (Fig. 2). Next, the Examiner asserts that Filippov teaches the claim limitation, “generating, by the pre-processor, an enhanced image based on the base values and the weighted delta values using a pixel-by-pixel addition”. Filippov teaches a reconstruction unit (214) (e.g., adder or summer 214) is configured to ass the transform block (213) (i.e., reconstructed residual block 213) to the prediction block (265) to obtain a reconstructed block (215) in the sample (pixel) domain, e.g., by adding sample-by-sample values of the reconstructed residual block (213) and the sample values of the prediction block (265) (Paragraph [0115]). Further, the Examiner interprets the reconstructed block is generated by a “pre-processor” since paragraph [0021] of applicant’s specification, states, the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. Further, Filippov teaches, embodiments of the encoder (20) and functions described herein, may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on a computer-readable medium or transmitted over communication media as one or more instructions or code and executed by a hardware-based processing unit (Paragraph [0317]). Therefore, under BRI, the Examiner interprets the reconstructed block to be a “pre-processor” since it may be implemented in software and stored on a computer-readable medium as one or more instructions executed by a hardware-based processing unit. Lastly, the Examiner asserts that Filippov discloses the limitation “compressing, by an encoder, the enhanced image”. Filippov teaches a pre-processor configured to receive the raw picture data (17) and perform pre-processing on the picture data to obtain a pre-processed picture (19). Pre-processing performed by the pre-processor (18) may comprise trimming, color format conversion, color correction, or de-noising (Paragraph [0078]). The video encoder is configured to receive the pre-processed picture data (19) and provide encoded picture data (21). The Examiner will maintain prior art Donovan and details of the rejection are below.
In regards to Claim 12, the Examiner asserts that Filippov teaches the claim language “generating, by a post-processor, base values and weighted delta values based on a reconstructed image”. Filippov teaches mode application unit (360) may be configured to perform the prediction per block based on reconstructed pictures, blocks, or respective samples to obtain the prediction block (365). Generating a prediction block (365) for a picture block of the current video slice is based on signaled intra prediction mode and data from previously decoded blocks of the current picture (Paragraphs [0151-153]). The Examiner interprets the “mode application unit” to be a “post-processor” since it receives the inter prediction parameters, intra prediction parameter and/or other syntax elements from the entropy decoding unit (304), and therefore, performs processing after the entropy decoding (Paragraph [0144]). Filippov also teaches the inverse quantization unit (310) may be configured to receive quantization parameters and quantized coefficients from the encoded picture data (21) (Paragraph [0145]). Further, the Examiner finds Filippov teaches the claim language “generating, by the post-processor, delta values based on the weighted delta values”. Specifically, Filippov teaches the inverse transform processing unit (212) is configured to apply the inverse transform of the transform applied to the transform processing unit (206) to obtain a reconstructed residual block in the sample (pixel) domain (Paragraph [0114]). The Examiner interprets the inverse transform processing unit to be a “post-processor” since it processes the data after the decoding via the decoding unit. Lastly, the Examiner finds Filippov teaches the limitation, “generating, by the post-processor, a modified image based on the base values and the delta values using a pixel-by-pixel addition”. Specifically, Filippov teaches the reconstruction unit (314) (e.g., adder or summer (314)) may be configured to add the reconstructed residual block (313), to the prediction block (365) to obtain a reconstructed block (315) in the sample (pixel) domain, e.g., by adding the sample values of the reconstructed residual block (313) and the sample values of the prediction block (365) (Paragraph [0147]). The Examiner will maintain prior art Donovan and Werness and details of the rejection are below.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 10 are rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 20120213435 A1, hereafter referred to as Donovan) in view of Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov).
Regarding Claim 1, Donovan teaches a method comprising: generating, by a (Paragraphs [0053], [0056-57], Donovan teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), base values (Paragraph [0010], Fig. 6, reference character 620, Donovan teaches identifying a tile in an image, where the image comprises a plurality of tiles including color data that is displayed by a plurality of pixels. A first base value is determined that is associated with the tile. A second base value is determined that is associated with the tile. The first and second base values are quantized to obtain a quantized first base value and a quantized second base value. Delta encoding is performed on the second quantized base value in relation to the quantized first base value to obtain a squeezed, quantized second base value. The quantized first base value and squeezed, quantized second base value are stored in a block of memory for purposes of color rendering for pixels in a tile.).
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and delta values based on an image (Paragraphs [0059], [0072-73], Fig. 2, reference character 210, Fig. 5A, reference character 540, Donovan teaches a base, delta, and index renderer (210) configured to interpolate and/or determine a base value, a delta value, and one or more indices for a tile of an image. A delta value is determined based on the difference between the first and second base values, wherein the first base value and the delta value are used for determining color and/or texture information for a pixel in a corresponding tile. Four delta values are determined for each tile.);
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generating, by the (Paragraphs [0053], [0056-57], Donovan teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), weighted delta values based on the delta values (Paragraphs [0072], [0079], Equation 1, Donovan teaches each tile is associated with a base value, a delta value, and a plurality of indices, wherein the indices [AltContent: arrow]provide weighting information for pixels in the tile. The delta value is added to the base value in an amount that is proportional to the decompressed index value for that pixel. The Examiner interprets that multiplying the delta value by a weighted index is the same as generating a weighted delta value based on the delta values since the claim is silent to how specifically the delta value is weighted.);
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generating, by the (Paragraphs [0053], [0056-57], Donovan teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), an (Paragraph [0081], Donovan teaches when rendering an image, the first and second base values are uncompressed and a delta value is determined based on the first and second base values. The first base value and the delta value are used for determining color and/or texture information for a pixel in a corresponding tile. The image comprises a plurality of tiles, each of which provides color and/or texture data that is displayable by a plurality of pixels for the image.) using a pixel-by-pixel addition (Paragraph [0079], Donovan teaches a color and/or texture value is determined for the pixels based on the interpolated base, the interpolated delta, and the index value for the pixel. The delta is added to the base value in an amount that is proportional to the decompressed index value for that pixel.) and compressing, by an encoder (Paragraph [0059], Donovan teaches the base, delta, and index renderer 210, quantizer/reverse quantizer 220, LSB compression/decompression mechanism 230, and delta encoder/decoder 240 are configurable for compressing color and/or texture information associated with pixels of one or more tiles of an image.),
Donovan does not explicitly disclose generating, by a pre-processor, base values and delta values based on an image; generating, by the pre-processor, weighted delta values based on the delta value; generating, by the pre-processor, an enhanced image based on the base values and the weighted delta values using a pixel-by-pixel addition and compressing, by an encoder, the enhanced image.
Filippov is in the same field of art of encoding by quantizing a residual block (difference/delta values) to reduce the amount of data to be transmitted/compressed. Further, Filippov teaches generating, by a pre-processor, base values (Paragraphs [0106], [0119-120], [0265], Fig. 2, Filippov teaches a mode selection unit (260) is configured to receive or obtain original picture data, e.g., an original block (203), and reconstructed picture data, e.g., filtered and/or unfiltered reconstructed samples or blocks of the same (current) picture and/or from one or a plurality of previously decoded pictures. The reconstructed picture data is used as a reference picture for prediction, e.g., inter-prediction, to obtain a prediction block. The prediction block (265) is used for calculation of residual block (205) i.e., by subtracting sample (pixel) values of the prediction block (265) from sample (pixel) values of the picture block (203). The Examiner interprets the “mode selection unit” to be a “pre-processor” since it generates the prediction block (265) prior to the encoding by the entropy encoding unit (270).)
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and delta values based on an image (Paragraphs [0106], Fig. 2, Filippov teaches a residual calculation unit (204) configured to calculate a residual block (205) also referred to as residual (205) based on the picture block (203) and a prediction block (265), e.g., by subtracting sample values of the prediction block (265) from sample values of the picture block (203), sample by sample (pixel by pixel) to obtain the residual block (205) in the sample (pixel) domain. The Examiner interprets the “residual calculation unit” to be a “pre-processor” since the residual block is calculated prior to/before the encoding by the entropy encoding unit (270) (see Fig. 2 below).);
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generating, by the pre-processor, weighted delta values based on the delta values (Paragraphs [0107-112], Filippov teaches the transform processing unit (206) may be configured to apply a transform, e.g., a discrete cosine transform (DCT) or discrete sine transform (DST), on the sample (pixel) values of the residual block (205) to obtain transform coefficients (207) in a transform domain. The transform coefficients may be referred to as transform residual coefficients and represent the residual block (205) in the transform domain. In order to preserve the residual block which is processed by forward and inverse transforms, additional scaling factors are applied as part of the transform process. The scaling factors are typically chosen based on certain constraints. Next, the quantization unit (208) may be configured to quantize the transform coefficients (207) to obtain quantized coefficients (209). The quantization unit (208) may be configured to output quantization parameters (QP), e.g., directly. As shown in Fig. 2, the transform processing unit (206) and the quantization unit (208) generate their output prior to the entropy encoding unit. Therefore, under BRI, the Examiner interprets the transform processing unit (and quantization unit) are “pre-processors” since they process the image data prior to encoding via the entropy encoding unit (270).);
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generating, by the pre-processor (Paragraph [0317], Filippov teaches embodiments, e.g. of the encoder (20) and functions described herein, e.g. with reference to the encoder (20), may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functions may be stored on a computer-readable medium or transmitted over communication media as one or more instructions or code and executed by a hardware-based processing unit. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), an enhanced image based on the base values and the weighted delta values using a pixel-by-pixel addition (Paragraph [0115], Filippov teaches the reconstruction unit (214) (e.g., adder or summer 214) is configured to add the transform block (213) (i.e., reconstructed residual block (213)) to the prediction block (265) to obtain a reconstructed block (215) in the sample (pixel) domain by adding-sample by sample the values of the reconstructed residual block (213) and the sample values of the prediction block (265).)
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and compressing, by an encoder, the enhanced image (Paragraphs [0078-79], [0098], Filippov teaches pre-processor (18) is configured to receive (raw) picture data (17) and perform pre-processing on the picture data (17) to obtain a pre-processed picture (19). Pre-processing performed by the pre-processor (18) may, e.g., comprise trimming, color format conversion, color correction, or de-noising. The video encoder (20) is configured to receive [AltContent: arrow]the pre-processed picture data (19) and provide encoded picture data (21).).
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan by replacing the processor with a “pre-processor” to generate the base values, delta values, weighted delta values, and the enhanced image to be inputted into the encoder that is taught by Filippov, to make the invention that reduces the amount of data to be compressed/transmitted for the image by transmitting data in the form of residuals (differences/ “deltas”) ; thus, one of ordinary skilled in the art would be motivated to combine the references since improved compression (and decompression) techniques that improve compression ratio with little to no sacrifice in picture quality are desirable (Filippov, Paragraph [0004]) and transforming the residual block and quantizing the residual block in the transform domain reduces the amount of data to be transmitted (compressed) by exploiting intra picture and inter picture information (Filippov, Paragraph [0071]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 10, Donovan in view of Filippov discloses the method of claim 1, wherein the generating of the enhanced image comprises summing the base values and the weighted delta values (Paragraph [0079], Fig. 5A, Donovan teaches at step (560), determining a color and/or texture value for the pixels based on the interpolated base value, the interpolated delta value, and the index value for the pixel. In particular, the delta value is added to the base value in an amount that is proportional to the decompressed index value for that pixel. The interpolated delta value is multiplied by the weighted index value for each pixel as shown in the equation below. The color value for each pixel is determined by the equation shown below (Equation 1). The Examiner interprets that by multiplying the interpolated delta value by a weighted index, the delta value is “weighted” and the claim is silent to specifically how the delta value is weighted.).
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Claims 2-6 are rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of
Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov) in further view of Goswami et al. (U.S. Patent Pub. No. 2023/0336745 A1, hereafter referred to as Goswami).
Regarding Claim 2, Donovan in view of Filippov teaches the method of claim 1.
Donovan in view of Filippov does not explicitly disclose applying an algorithm to each pixel of an input image to generate the image.
Goswami is in the same field of art of performing image compression by generating base and delta values to render higher quality graphics or images. Further, Goswami teaches applying an algorithm to each pixel of an input image to generate the image (Paragraphs [0051], [0028], Goswami teaches a “shape walker” which utilizes an algorithm known as DDA (digital differential analyzer) line generating algorithm to determine whether a pixel intersects with an edge of a primitive (trapezoid, curve, etc.) for each tile in an image. The technique may continue by traversing row-by-row of the tile to identify, based on the function equation any pixels that intersect with the edge of the primitive. The Examiner interprets that since the DDA line generating algorithm is applied to every pixel in every tile, that an algorithm is applied to each pixel of the input image. Additionally, under Broadest Reasonable Interpretation, the Examiner interprets that since the claim is silent to the type of algorithm applied to the pixels, that any algorithm applied to the pixels meets the limitation.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan by applying an algorithm to each pixel in each tile of an input image to determine whether a pixel intersects with an edge or primitive/shape that is taught by Goswami, to make the invention that determines which pixels require more fine-grained pixel-level analytic anti-aliasing and which do not require anti-aliasing to save power; thus, one of ordinary skilled in the art would be motivated to combine the references since it enables rendering high-quality images while operating on a low power budget (Goswami, Paragraph [0027]).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 3, Donovan in view of Filippov in further view of Goswami discloses the method of claim 2, wherein applying the algorithm to each pixel of the input image comprises: selecting a tile of pixels of the input image (Abstract, Fig. 6, reference character 610, Donovan teaches identifying a tile in an image, wherein the image comprises a plurality of tiles including color data that is displayed by a plurality of pixels.);
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applying the algorithm to a first portion of the pixels of the tile (Paragraphs [0051-52], Fig. 4B, Goswami teaches a shape walker for performing an algorithm known as DDA (digital differential analyzer) line generating algorithm to determine whether a pixel intersects with an edge of a primitive. The shape walker may process only the pixels within the bounding box, rather than the entire tile. See Fig. 4B below.);
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and applying the algorithm to a second portion of the pixels of the tile (Paragraphs [0051-53], Goswami teaches a shape walker may be able to process for each primitive in a tile, a single edge at a time. For example, in the example shown in Fig. 4B, the shape walker may process the left edge separately from the top edge.).
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In regards to Claim 4, Donovan in view of Filippov in further view of Goswami discloses the method of claim 3, further comprising: selecting at least two pixels in the tile of pixels as the first portion of the pixels (Paragraphs [0052-53], Fig. 4B, Goswami teaches an example of determining whether a pixel intersects with the edge of a trapezoid using a shape walker. The shape walker may analyze each pixel position within a tile to determine whether the pixel overlaps with an edge of a primitive (e.g. trapezoid or curve). A shape walker may process for each primitive within a tile, a single edge at a time. For example, in Fig. 4B, a shape walker may process only the left edge of the trapezoid. The Examiner interprets that the shape walker selects at least two pixels in a first portion of tiles by processing only the left edge of the trapezoid as shown in Fig. 4B.); and selecting at least two pixels in the tile of pixels as the second portion of the pixels (Paragraphs [0052-53], Fig. 4B, Goswami teaches an example of determining whether a pixel intersects with the edge of a trapezoid using a shape walker. The shape walker may analyze each pixel position within a tile to determine whether the pixel overlaps with an edge of a primitive (e.g. trapezoid or curve). A shape walker may process for each primitive within a tile, a single edge at a time. For example, in Fig. 4B, a shape walker may process only the top edge of the trapezoid. The Examiner interprets that the shape walker selects at least two pixels in a first portion of tiles by processing only the top edge of the trapezoid as shown in Fig. 4B.).
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In regards to Claim 5, Donovan in view of Filippov in further view of Goswami discloses the method of claim 2, wherein applying the algorithm to each pixel of the input image comprises: selecting a tile of pixels of the input image (Abstract, Fig. 6, reference character 610, Donovan teaches identifying a tile in an image, wherein the image comprises a plurality of tiles including color data that is displayed by a plurality of pixels.); and applying the algorithm to all of the pixels of the tile to generate one of the delta values (Paragraph [0072], Donovan teaches first identifying a pixel in an image. Then, a delta value is determined based on the difference between the first and second base values, wherein the first base value and the delta value are used for determining color and/or texture for a pixel in a corresponding tile. Each tile is associated with a base value, delta value, and a plurality of indices, wherein the indices provide weighting information for the pixels in the tile. The Examiner interprets that calculating the difference between the first and second base values (performing subtraction) to determine the delta value for the pixels in a tile is an algorithm, specifically a subtraction algorithm, since the claim is silent to the specific type of algorithm applied to the pixels in the tile.).
In regards to Claim 6, Donovan in view of Filippov in further view of Goswami discloses the method of claim 2, wherein applying the algorithm to each pixel of the input image comprises: selecting a tile of pixels of the input image (Abstract, Fig. 6, reference character 610, Donovan teaches identifying a tile in an image, wherein the image comprises a plurality of tiles including color data that is displayed by a plurality of pixels.); applying the algorithm to all of the pixels of the tile (Paragraphs [0059], [0071], Fig. 5A, Donovan teaches for each pixel in a tile, determining a color value based on base and delta values that is weighted by an index value corresponding to the pixel. Fig. 5A is a flow diagram showing the steps required for determining a color value for a pixel in an image. Steps of the method include: at (510) identifying a pixel in an image, at (520) identifying one or more tiles associated with the pixel, at (530) determining an interpolated base by interpolating decompressed bases of the one or more tiles, at (540) determining an interpolated delta by interpolating deltas of the one or more tiles, at (550) determining an index for the pixel, at (560), determining a color value for the pixel based on the interpolated base, the interpolated delta, and the index. The Examiner interprets that the steps shown in Fig. 5A are a sequence of steps or instructions designed to perform a specific task or function and therefore are steps of an algorithm.); and assigning a value generated by the algorithm to each of the pixels of the tile (Paragraphs [0006], [0071], Fig. 5A, reference character 560, Fig. 2, reference character 210, Donovan teaches determining a color value for each pixel based on the interpolated base value, interpolated delta value, and index. The operations performed by the flow diagram in Fig. 5A are implemented by the base, delta, and index renderer (210) of codec (200) in Fig. 2.).
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Claim 7 is rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of
Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov) in further view of Goswami et al. (U.S. Patent Pub. No. 2023/0336745 A1, hereafter referred to as Goswami) in further view of Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim).
Regarding Claim 7, Donovan in view of Filippov in further view of Goswami teaches the method of claim 2 wherein the generating of the base values and the delta values comprises: (Paragraph [0099], Fig. 19, Goswami teaches calculating the difference between a corresponding pixel in the sequence and a previous pixel in the sequence.); and the delta values being a result of the subtraction (Paragraph [0099], Fig. 19, Goswami teaches a plurality of delta values having non-zero delta values and zero delta values, each delta value representing a difference between a corresponding pixel in the sequence and a previous pixel in the sequence.).
Donovan in view of Filippov in further view of Goswami does not explicitly disclose wherein the generating of the base values and the delta values comprises: subtracting the input image from a result of applying the algorithm to each pixel of the input image.
Kim is in the same field of art of efficiently compressing image frames to reduce cost and time associated with storing and transmitting large image and video files. Further, Kim teaches wherein the generating of the base values and the delta values comprises: subtracting the input image from a result of applying the algorithm to each pixel of the input image (Col. 45, lines 36-43, Kim teaches temporally predicting the positions, attributes, and textures by taking the difference between the value at the current resampled rate minus a corresponding value, e.g. motion compensated value, from the reference frame.).
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Filippov by calculating deltas/differences between pixels by taking the difference (subtracting) between the value at current resampled frame minus a corresponding value, from the reference frame that is taught by Kim, to make the invention that transmits the difference between consecutive/related images rather than the values themselves; thus, one of ordinary skilled in the art would be motivated to combine the references to decrease the quantity of data needed to represent images or videos (Filippov, Paragraph [0004]) .
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claim 9 is rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov) in further view of Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim) in further view of Astle (U.S. Patent No. 5,590,064, hereafter referred to as Astle).
Regarding Claim 9, Donovan in view of Filippov discloses the method of claim 1.
Donovan in view of Filippov does not explicitly disclose wherein the generating of the weighted delta values comprises: applying a weight to the delta values having a value below a threshold value; and assigning the delta values having a value above a threshold value as the weighted delta values.
Kim is in the same field of art of efficiently compressing image frames to reduce cost and time associated with storing and transmitting large image and video files. Further, Kim discloses wherein the generating of the weighted delta values comprises: applying a weight to the delta values having a value below a threshold value (Col. 65, lines 60-64, Claim 7, Kim teaches for samples that are too far from a sample x in terms of depth distance, e.g., exceed a distance threshold T, may be excluded when processing sample x. Other samples, that are below the distance threshold T, may be weighted or prioritized in processing again based on their distance. The Examiner interprets that the difference in depth distance between samples is a “delta” value since the claim is silent to the definition of delta value.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Filippov by applying a weight to the differences between values below a threshold that is taught by Kim, to make the invention that prioritizes or applies weights in processing based on their distances; thus, one of ordinary skilled in the art would be motivated to combine the references since differences/deltas below a certain threshold to prioritize differences that may be smaller, i.e., not noticeable. Therefore, weights of samples may be prioritized based on how similar or dissimilar the attributes are (Kim, Col. 65, lines 64-67). Further, difference between similar pixels would be small, however, weighting may help finer details to be maintained after the encoding/compression of the image.
Donovan in view of Filippov in further view of Kim does not explicitly disclose assigning the delta values having a value above a threshold value as the weighted delta values.
Astle is in the same field of art of reducing the bit rate for a given video/image quality and/or improving video/image quality at a constant bit rate. Further, Astle discloses assigning the delta values having a value above a threshold value as the weighted delta values (Col. 14, lines 4-17, Astle teaches if the magnitude of the difference between a spatially filtered pixel and the corresponding unfiltered source pixel is less than the noise threshold value, then the differences between the adjacent pixels are assumed to be due to noise and the spatially filtered pixel value is retained. Otherwise, the pixel differences are assumed to be due to true signal differences. In that case, the filtered pixel is set to a value not more than a noise threshold away from the unfiltered source pixel value.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Kim by spatially filtering a region of change in an image in order to reduce noise and improve image quality by applying a threshold condition to the differences between pixels that is taught by Astle, to make the invention that avoids problems associated with transitions between changed regions and unchanged regions; thus, one of ordinary skilled in the art would be motivated to combine the references to increase image quality by providing an inexpensive way to remove random noise from stationary areas in a video sequence and for reducing the spatial information present in moving or otherwise changing areas in a frame or image (Astle, Col. 10, lines 23-29).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claim 11 is rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of
Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov) in further view of Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim).
Regarding Claim 11, Donovan in view of Filippov discloses the method of claim 1.
Donovan in view of Filippov does not explicitly disclose wherein the compressing of the enhanced image is codec-agnostic.
Kim is in the same field of art of efficiently compressing image frames to reduce cost and time associated with storing and transmitting large image and video files. Further, Kim teaches wherein the compressing of the enhanced image is codec-agnostic (Col. 2, lines 51-67, Col. 3, lines 1-2, Kim teaches the encoder may utilize various image or video encoding techniques to encode the one or more image frames. For example, the encoder may utilize a video encoder in accordance with the High Efficiency Video Coding (HEVC/H.265) standard or other suitable standards such as, Advanced Video Coding (AVC/H.265) standard, the AOMedia Video 1 (AV1) video coding format produced by the Alliance for Open Media (AOM), etc. In some embodiments, the encoder may utilize an image encoder in accordance with Motion Picture Experts Group (MPEG), a Joint Photography Experts Group (JPEG) standard, an International Telecommunication Union-Telecommunication standard (e.g. ITU-T standard), etc.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Filippov by designing encoding strategies to work effectively across multiple video coding standards, such as HEVC/H.265, AVC, AV1, MPEG, JEPG, ITU-T, etc. that is taught by Kim, to make the invention that enables flexible deployment in diverse streaming environments while maintaining optimal performance; thus, one of ordinary skilled in the art would be motivated to combine the references to improve adaptability to different content types and delivery constraints in order to maintain/balance video quality, bitrate, and encoding speed.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Claims 12 and 15-20 are rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of Werness et al. (U.S. Patent Pub No. 2013/0022265 A1, hereafter referred to as Werness) in further view of Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov).
Regarding Claim 12, Donovan teaches a method comprising: generating, by a (Paragraphs [0053], [0056-57], Donovan teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), base values and weighted delta values based on a reconstructed image (Paragraphs [0031], [0095], Fig. 7, Donovan teaches a method for performing reverse quantization and reverse delta encoding when decompressing compressed base and delta values for a tile of an image. This method is performed when determining a color and a texture value for a pixel within a tile. A delta value is determined from the decompressed first and second base values. The decompressed base and delta values are combined with a weighted index value for the pixel to determine the color and/or texture value.);
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generating, by the (Paragraphs [0053], [0056-57], Donovan teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), a modified image based on the base values and the delta values (Paragraph [0059], Donovan teaches the base, delta, and index renderer (210), quantizer/reverse quantizer (220), LSB compression/decompression mechanism (230), and delta encoder/decoder (240) configurable for compressing color and/or texture information associated with pixels of one or more tiles of an image, and is also configurable for decompressing the compressed color and texture information for pixels of an image for displaying the image. Specifically, the delta decoder provides for delta decoding of the second base value during decompression. The Examiner interprets that by decompressing the compressed color and/or texture information for pixels in an image to display the image is generating a “modified image” since the claim is silent to how specifically the image is modified.) using a pixel-by-pixel addition (Paragraph [0079, Donovan teaches determining a color and/or texture value is determined for the pixels based on the interpolated base, the interpolated delta, and the index value for the pixel. In particular, the delta is added to the base value in an amount that is proportional to the decompressed index value for that pixel. The color value is determined by Equation 1, as follows:
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).
Donovan does not explicitly disclose generating, by the post-processor, delta values based on the weighted delta values.
Werness is in the same field of art of encoding the true color information for an image, and decoding, reconstructing, and displaying the decompressed true color image data. Further, Werness teaches generating, by the (Paragraphs [0054], [0057], Werness teaches a computing system (100) capable of implementing embodiments of the present disclosure. Computing system (100) may include at least one processor (110) and a system memory (140). Processors (110) and/or (120) may perform and/or be a means for performing, either alone or in combination with other elements, one or more of identifying, determining, quantizing, reverse quantization, delta encoding, delta decoding. In addition, in light of Applicant’s specification (paragraph [0021]), the Examiner interprets the “pre-processor” can be “software implementations that use processor and memory of a device including the encoder 110 and decoder 115”. As stated in Applicant’s disclosure.), delta values based on the weighted delta values (Paragraphs [0070], [0073], Werness discloses decompressing a pixel by determining the 4 nearest blocks to the pixel. Then, for each block, decompressing its weights and values, giving a base and delta value and weight. The colors are computed based on the base and delta values. Four tiles give four (base, delta) pairs for the pixel being interpolated. The interpolated weight is used to compute the four interpolated colors from these four pairs, using an expression of the form base+delta*weight/16. The Examiner interprets that since the weights and values can be decompressed to give the base, delta, and weight, the delta values are generated based on the delta values and the weight applied. In addition, the claim is silent to how the delta values are generated based on the weighted delta values.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan by decompressing each pixel’s weights and values to generate base, delta, and weight values and computing the color of the pixel based on the values and weights that is taught by Werness, to make the invention that decodes compressed true color image data to generate a lossless image; thus, one of ordinary skilled in the art would be motivated to combine the references since the cost of storing true color information of each of the pixels in an image is prohibitively high and storing compressed true color information decreases the amount of memory required while providing a lossless storage and display option (Werness, Paragraphs [0003-5]).
Donovan in view of Werness does not explicitly disclose generating, by a post-processor, base values and weighted delta values based on a reconstructed image; generating, by the post-processor, delta values based on the weighted delta values; and generating, by the post-processor, a modified image based on the base values and the delta values using a pixel-by-pixel addition.
Filippov is in the same field of art of providing decoded picture data from the encoded picture data. Further, Filippov teaches generating, by a post-processor, base values (Paragraphs [0151-153], [0144], Fig. 3, Filippov teaches mode application unit (360) may be configured to perform the prediction (intra or inter prediction) per block based on reconstructed pictures, blocks, or respective samples (filtered or unfiltered) to obtain the prediction block (365). Generating prediction block (365) for a picture block of the current video slice based on a signaled intra prediction mode and data from previously decoded blocks of the current picture. The prediction blocks may be produced from one of the reference pictures within one of the reference picture lists. The Examiner interprets the “mode application unit” to be a “post-processor” since it receives the inter prediction parameters, intra prediction parameter and/or other syntax elements from the entropy decoding unit (304), and therefore, performs processing after the entropy decoding (see Para. [0144]).)
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and weighted delta values based on a reconstructed image (Paragraph [0145], Fig. 3, Filippov teaches the inverse quantization unit (310) may be configured to receive quantization parameters (QP) and quantized coefficients from the encoded picture data (21).); generating, by the post-processor, delta values based on the weighted delta values (Paragraph [0114], Filippov teaches the inverse transform processing unit (212) is configured to apply the inverse transform of the transform applied to the transform processing unit (206), e.g., an inverse discrete cosine transform (DCT) or inverse discrete sine transform (DST) or other inverse transforms, to obtain a reconstructed residual block in the sample (pixel) domain. The reconstructed residual block (213) may also be referred to as transform block (213). The Examiner interprets the inverse transform processing unit to be a “post-processor” since it processes the data after the entropy decoding unit (304).);
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and generating, by the post-processor, a modified image (Paragraph [0088], Fig. 1A, Filippov teaches the post-processor (32) of destination device (14) is configured to post-process the decoded picture data (31) (also called reconstructed picture data), e.g., the decoded picture (31), to obtain post-processed picture data (33), e.g., a post-processed picture (33). The post-processing performed by the post-processing unit (32) may comprise, e.g., color formal conversion, color correction, trimming, or re-sampling, or any other processing, e.g., for preparing the decoded picture data (31) for display.) based on the base values and the delta values using a pixel-by-pixel addition (Paragraph [0147], Fig. 3, Filippov teaches the reconstruction unit (314) (e.g., adder or summer (314)) may be configured to add the reconstructed residual block (313), to the prediction block (365) to obtain a reconstructed block (315) in the sample domain, e.g., by adding the sample values of the reconstructed residual block (313) and the sample values of the prediction block (365).).
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Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Werness by adding/summing the reconstructed residual block (delta values) and the prediction block (base values) to obtain the reconstructed block (modified image) that is taught by Filippov, as well as performing post-processing (post-decoding) steps in order to generate the decoded image; to make the invention that reconstructs a reconstructed block based on the prediction block and the reconstructed residual block by adding them together sample-by-sample (pixel-by-pixel); thus, one of ordinary skilled in the art would be motivated to combine the references since there is a need for improved decompression techniques that improve compression ratio with little to no sacrifice in picture quality (Filippov, Paragraph [0004]). Further, adding the delta values and base values together after being compressed is essential for recovering the original pixel value of the input image.
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
In regards to Claim 15, Donovan in view of Werness in further view of Filippov discloses the method of claim 12, wherein the generating of the modified image comprises summing the base values and the delta values (Paragraph [0069], Donovan teaches to decompress a pixel, selecting the four blocks surrounding that pixel to determine a decompressed index, four base values, and four delta values, wherein the first base value and a second base value in compressed form are stored per block. A delta value is determined based on the difference between the decompressed first and second base values, wherein the first base value and the delta value are used for interpolation. The delta value is added to the base value in an amount proportional to the decompressed index for that pixel.).
In regards to Claim 16, Donovan in view of Werness in further view of Filippov discloses the method of claim 12, further comprising generating the reconstructed image by decompressing a compressed image (Paragraphs [0008], [0013], [0058], Fig. 7, Donovan teaches a codec configured to perform image decompression by performing reverse quantization and reverse delta encoding. The image decoder is configured to receive the compressed color and texture information for the image, decode the information, and produce a displayable image.).
In regards to Claim 17, Donovan in view of Werness in further view of Filippov discloses the method of claim 12, further comprising: generating a restored image based on the modified image using an algorithm applied to each pixel of the modified image (Paragraph [0058], Donovan teaches a decoder for receiving the compressed color and/or texture information, decoding the information, and producing a displayable image. The decoder performs delta decoding of the second base value during decompression for each pixel in a tile. The Examiner interprets delta decoding to be an algorithm because it involves a sequence of instructions to solve a specific problem or perform a computation.).
In regards to Claim 18, Donovan in view of Werness in further view of Filippov discloses the method of claim 17, wherein the generating of the restored image comprises: selecting a tile of pixels of the modified image (Paragraph [0096], Fig. 7, reference character 710, Donovan teaches at (710), identifying a tile in an image. The tile is associated with one or more pixels. Information related to color and/or texture is determined based on the decompressed base, delta, and index information for a particular pixel of the tile. The image comprises a plurality of tiles, each of which provides color and/or texture data that is displayable by a plurality of pixels for the image.); applying the algorithm to a first portion of the pixels of the tile (Paragraph [0106], Fig. 8, reference character 821, Donovan teaches decompressing pixel (5,5) (at “A”) by decompressing and determining the base and delta values associated with tile 821 (e.g. at A) to compute the result using the decompressed index. The Examiner interprets that a single pixel within the tile is a “portion” since the claim is silent to the number of pixels.);
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and applying the algorithm to a second portion of the pixels of the tile (Paragraph [0106], Fig. 8, reference characters 821-824, Donovan teaches decompressing the other pixels shown as +’s in Fig. 8. The four bases associated with the tiles 821-824 are bilinearly interpolated (e.g. between the four bases Abase, Bbase, Cbase, and Dbase). Also, the four deltas associated with the tiles 821-824 are bilinearly interpolated (e.g. between Adelta, Bdelta, Cdelta, Ddelta). The interpolated base and delta values are then weighted using decompressed and interpolated averaged index values. The base and delta values are determined. The Examiner interprets the pixels located at the +’s as a second portion of the pixels in the tile since the claim is silent to the number of pixels.).
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In regards to Claim 19, Donovan in view of Werness in further view of Filippov discloses the method of claim 18, further comprising: selecting at least two pixels in the tile of pixels as the first portion of the pixels (Paragraph [0117], Fig. 11, Donovan teaches applying an interpolation algorithm to the pixel’s North (N), South (S), West (W), and East(E) neighbors, as shown in Fig. 11. If any pixels were valid, the interpolation algorithm returns the rounded average weight.);
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and selecting at least two pixels in the tile of pixels as the second portion of the pixels (Paragraph [0117], Fig. 11, Donovan teaches applying an interpolation algorithm to the pixel’s Northeast (NE), Southeast (SE), Northwest (NW), and Southwest (SW) neighbors, as shown in Fig. 11. If the N, S, W, and E neighbors were invalid, the interpolation algorithm looks at the NE, SE, NW, and SW neighbors and returns the rounded average weight of the valid neighbors.).
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In regards to Claim 20, Donovan in view of Werness in further view of Filippov discloses the method of claim 18, wherein the generating of the restored image comprises: selecting a tile of pixels of the modified image (Paragraph [0096], Fig. 7, reference character 710, Donovan teaches at (710), identifying a tile in an image. The tile is associated with one or more pixels. Information related to color and/or texture is determined based on the decompressed base, delta, and index information for a particular pixel of the tile. The image comprises a plurality of tiles, each of which provides color and/or texture data that is displayable by a plurality of pixels for the image.); and assigning a value generated by the algorithm to each of the pixels of the tile (Paragraph [0104], Donovan teaches using the reproduced first base value and the delta value for determining color and/or texture values for pixels in the corresponding tile.).
Claim 14 is rejected under 35 U.S.C. 103(a) as being unpatentable over Donovan et al. (U.S. Patent Pub. No. 2012/0213435 A1, hereafter referred to as Donovan) in view of Werness et al. (U.S. Patent Pub No. 2013/0022265 A1, hereafter referred to as Werness) in further view of Filippov et al. (U.S. Patent Pub. No. 20260006255 A1, hereafter referred to as Filippov) in further view of Astle (U.S. Patent No. 5,590,064, hereafter referred to as Astle.).
Regarding Claim 14, Donovan in view of Werness in further view of Filippov discloses the method of claim 12.
Donovan in view of Werness in further view of Filippov does not explicitly disclose wherein the generating of the delta values comprises: applying a weight to the weighted delta values having a value below a threshold value; and assigning the weighted delta values having a value above the threshold value as the delta values.
Astle is in the same field of art of reducing the bit rate for a given video/image quality and/or improving video/image quality at a constant bit rate. Further, Astle teaches applying a weight to the weighted delta values having a value below a threshold value (Col. 13, lines 48-67, Col. 14, lines 1-17, Astle teaches spatially filtering a region of change in order to reduce noise and improve the final quality of the image. Spatial filtering is appropriate when neighboring pixels can be correlated with one another. The spatially filtered pixels may be adjusted so that they do not differ by more than a specified threshold value from the source pixels. Then, the spatially filtered pixels are compared to the unfiltered source pixels. If the magnitude of the difference between a spatially filtered pixel and the corresponding unfiltered source pixel is less than the noise threshold value, then the differences between the adjacent pixels are assumed to be due to noise and the spatially filtered pixel value is retained. The Examiner interprets that “adjusting” the spatially filters so that they do not differ by more than a specified threshold effectively applies a weight.); and assigning the weighted delta values having a value above the threshold value as the delta values (Col. 14, lines 4-17, Astle teaches if the magnitude of the difference between a spatially filtered pixel and the corresponding unfiltered source pixel is less than the noise threshold value, then the differences between the adjacent pixels are assumed to be due to noise and the spatially filtered pixel value is retained. Otherwise, the pixel differences are assumed to be due to true signal differences. In that case, the filtered pixel is set to a value not more than a noise threshold away from the unfiltered source pixel value.).
Therefore, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Donovan in view of Werness in further view of Filippov by spatially filtering a region of change in an image in order to reduce noise and improve image quality by applying a threshold condition to the differences between pixels that is taught by Astle, to make the invention that avoids problems associated with transitions between changed regions and unchanged regions; thus, one of ordinary skilled in the art would be motivated to combine the references to increase image quality by providing an inexpensive way to remove random noise from stationary areas in a video sequence and for reducing the spatial information present in moving or otherwise changing areas in a frame or image (Astle, Col. 10, lines 23-29).
Thus, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Allowable Subject Matter
Claims 8 and 13 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding Claim 8, no prior art teaches wherein the generating of the weighted delta values comprises: applying a weight to each of the delta values, wherein the weight is in a range of 0.5 to 2.0.
In regards to Claim 13, no prior art teaches wherein the generating of the delta values comprises: applying a weight to each of the weighted delta values, wherein the weight is in a range of 0.5 to 2.0.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SYDNEY L BLACKSTEN whose telephone number is (571)272-7651. The examiner can normally be reached 8:30am-4:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Oneal Mistry can be reached at 313-446-4912. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/SYDNEY L BLACKSTEN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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