DETAILED ACTION
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 .
Priority
Applicant claims the benefit of National Stage Application PCT/US23/61473, filed on 01/27/2023. Claims 1-20 have been afforded the benefit of this filing date.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/20/2024 is being considered by the Examiner. The submission is in compliance with the provisions of 37 CFR 1.97.
Amendment
Applicant submitted amendments on 03/20/2024. The examiner acknowledges the amendment and has reviewed the claims accordingly.
Status of Claims
Claims 1-20 are pending.
Specification
The disclosure is objected to because of the following informalities:
In paragraph [0010], “a pixel tile selection blocks should read “pixel tile selection blocks.”
In paragraph [0045], “The subtraction can be pixel-by-pixel subtraction” is missing a period at the end of the sentence.
In paragraph [0048], “In an example implementation, compressed the enhanced image” should read “In an example implementation, compressing the enhanced image.”
In paragraph [0049], “For example, Foe example” should read “For example.”
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
With respect to Claim 12, the claim recites the following, each of which renders the claim indefinite:
“the image” on line 2 (unclear antecedent basis); it is unclear whether the image recited in line 2 of claim 2 is referring to the “image” recited in line 2 of claim 1 or the “enhanced image” recited in line 6 of claim 1.
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 10-11 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 Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim).
Regarding Claim 1, Donovan teaches a method comprising: generating 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 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 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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Donovan does not explicitly disclose generating an enhanced image based on the base values and the weighted delta values; and compressing the enhanced 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 generating an enhanced image based on the base values and the weighted delta values (Col. 16, lines 13-47, Col. 101, lines 12-36, Fig. 2C, Fig. 9D, Kim teaches a 3D motion compensation & delta vector prediction module (254), which applies a temporal prediction to the geometry/texture/attributes of the resampled point cloud points into patches. The prediction residuals may be stored into images. Regarding spatial changes for points of the patches between the reference frame and a current frame, the 3D motion compensation & delta vector prediction module (254) may determine respective vectors for each of the points indicating how the points moved from the reference frame to the current frame. The 3D motion compensation & delta vector prediction module (254) may then encode the motion vectors using different image parameters to generate a relative motion patch image. For example, changes in the X direction for a point may be represented by the amount of red included at the point in a patch image that includes the point. Similarly, the changes in the Y direction for a point may be represented by an amount of blue included at the point in a patch that includes the point. Other characteristics of an image included in a patch image may be adjusted to indicate motion of points included in a patch between a reference frame for the patch and a current frame for the patch. Next, an updated color patch is generated. The updated color patch may encode residual values indicating differences in colors of the points of the point cloud included in the patch between the reference point cloud and the current point cloud. When there are no more patches to evaluate, the patch images are packed into one or more image frames. Any remaining spaces in the one or more image frames that are not occupied by patch images are padded. Padding may construct new pixel blocks that are replicas of, or are to some degree similar to, pixel blocks that are on the edges of image patches. This approach may reduce the number of bytes required to encode an image frame comprising of patch images and padding. The Examiner interprets the reference frame points to be the “base values” and the motion vectors (delta) represented by an “amount” (weight) of a color (red, blue, green) as the weighted delta values. The motion vectors indicate how the points moved or changed between a reference frame and a current frame and are therefore being interpreted by the Examiner as “delta values.” Additionally, the Examiner interprets the padded image to be an enhanced image since the claim is silent to the definition of enhanced image.);
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and compressing the enhanced image (Col. 101, lines 37-39, Col. 16, lines 1-12, Fig. 9D, Fig. 2C, Kim teaches, at (945) in Fig. 9D shown above, encoding the image frame(s). An encoder for inter-point cloud frames, such as encoder (250) in Fig 2C, may generate more compact, compressed point cloud information by not repeating information included in a reference image frame, and instead communicating differences between the reference frames and a current state of the point cloud (current frame).)
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 adding a step of prior to compressing the image of enhancing the image by padding the image using techniques such as linear extrapolation, inpainting, etc. to fill the non-occupied pixels with values such that the resulting image is better suited for video/image compression and compressing the padded image that is taught by Kim, to make the invention that generates an enhanced image as input to the compression encoder; thus, one of ordinary skilled in the art would be motivated to combine the references since padding the image prior to compression may minimize incongruences between a patch image and the padding. For example, padding may construct new pixel blocks that are replicas of, or are to some degree similar to, pixel blocks that are on edges of image patches. Since an image encoder may encode based on differences between adjacent pixels, such an approach may be used to reduce the number of bytes required to encode an image frame comprising of patch images and padding (Kim, Col. 27, lines 55-65).
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 Kim 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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In regards to Claim 11, Donovan in view of Kim discloses the method of claim 1, 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.).
Claims 2-7 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 Kim et al. (U.S. Patent No. 11,798,196 B2, hereafter referred to as Kim) 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 Kim teaches the method of claim 1.
Donovan in view of Kim 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 in view of Kim 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 Kim 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 Kim 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 Kim 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 Kim 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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In regards to Claim 7, Donovan in view of Kim in further view of Goswami discloses the method of claim 2, 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.); the subtraction being a pixel-by-pixel subtraction (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.).
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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 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 Kim discloses the method of claim 1, 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.).
Donovan in 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.
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).
Regarding Claim 12, Donovan teaches a method comprising: generating 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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and generating 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.).
Donovan does not explicitly disclose generating 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 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]) .
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 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 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 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 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 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 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 Astle (U.S. Patent No. 5,590,064, hereafter referred to as Astle.).
Regarding Claim 14, Donovan in view of Werness discloses the method of claim 12.
Donovan in view of Werness 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 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.
Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Miller et al. (U.S. Patent No. 6,181,822 B1)
Guleryuz et al. (U.S. Patent Pub. No. 2025/0045968 A1)
Conclusion
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-5pm.
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/SYDNEY L BLACKSTEN/Examiner, Art Unit 2674
/ONEAL R MISTRY/Supervisory Patent Examiner, Art Unit 2674
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