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 .
Status of Claims
This communication is in response to the Application Filed on 04/30/2024
Claims 1–20 are pending in this application.
Drawings
The drawing(s) filed on 04/30/2024 are accepted by the Examiner.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 06/10/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 18–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because they cover both statutory and non-statutory embodiments (under the broadest reasonable interpretation of the claim when read in light of the specification and in view of one skilled in the art) and embraces subject matter that is not eligible for patent protection and therefore is directed to non-statutory subject matter.
“[a] transitory, propagating signal … is not a “process, machine, manufacture, or composition of matter.” Those four categories define the explicit scope and reach of subject matter patentable under 35 U.S.C. § 101; thus, such a signal cannot be patentable subject matter.” (In re Petrus A.C.M. Nuijten; Fed Cir, 2006-1371, 9/20/2007).
Specifically, Applicant’s specification describes at paragraph ¶ [0082] of the specification recites: “The term computer readable media as used herein may include computer storage media. Computer storage media may include volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, or program modules” describes and as a result is drawn to a recording medium that covers both transitory and non-transitory embodiments. Thus, the claims are not eligible subject matter. It is recommended to amend and narrow the claims to cover only statutory embodiments to avoid a rejection under 35 U.S.C. § 101 by adding the limitation "non-transitory" to the claims.
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 (i.e., changing from AIA to pre-AIA ) 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 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 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 non-obviousness.
Claim(s) 1–6, 11–16, 18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Motilla et al. (US 20230325977 A1, hereafter, "Motilla") in view of Kim et al. (US 20210166304 A1, hereafter, “Kim) further in view of Guede et al. (US 20230377204 A1, hereafter, "Guede").
Regarding claim 1, Motilla teaches A method for upscaling a content using an upscaling model (See Motilla, [Abstract], A computer-implemented method for image upscaling at a client device is provided), the method comprising:
determining an output display resolution of a visual display adapted to display the content (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display. Note: The native resolution must be known to make the image suitable for the client display);
[determining an input resolution of the content to be requested based on the display resolution and an upscaling factor];
determining a tile size of a tile of the content to be processed by the upscaling model (See Motilla, ¶ [0048], According to a second step 120, the client device determines a first group of image portions to apply one of a plurality of upscaling processes to), the tile size indicating a number of pixels and an aspect ratio of the tile (See Motilla, ¶ [0047], The image data received at the client device is divided, or split, into image portions. Image portions may also be referred to herein as tiles, …, For example, the tile size may be 256 x 256 pixels, or 128 x 128 pixels, or any other size deemed suitable. Aspect ratios of the tiles other than 1:1 are possible), and the tile being a segment of the content to be processed by the upscaling model (See Motilla, ¶ [0047], The image data received at the client device is divided, or split, into image portions);
[selecting the upscaling model from a plurality of upscaling models to be used for upscaling the content based on the tile size and the upscaling factor, each upscaling model being trained with a particular tile size and a particular upscale factor for increasing the resolution of the content];
in response to receiving the content according to the input resolution, converting the content to enhance the resolution of the content using the upscaling model (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display); and
rendering the converted content on the visual display (See Motilla, ¶ [0006], Selecting the most suitable upscaling process for a chosen group of image portions helps to achieve overall efficiency of the video upscaling process whilst maintaining a high-resolution image displayed by the client at the client display).
However, Motilla fail(s) to teach determining an input resolution of the content to be requested based on the display resolution and an upscaling factor; selecting the upscaling model from a plurality of upscaling models to be used for upscaling the content based on the tile size and the upscaling factor, each upscaling model being trained with a particular tile size and a particular upscale factor for increasing the resolution of the content.
Kim, working in the same field of endeavor, teaches: determining an input resolution of the content to be requested based on the display resolution and an upscaling factor (See Kim, ¶ [0095], For example, when the resolution of the input image is 4K UHD of 3840×2160 and the identified upscaling ratio is 2, the processor 110 may estimate that the resolution of the original image is FHD of 1920×1080. As another example, when the resolution of the input image is 4K UHD of 3840×2160 and the identified upscaling ratio is 2.1, the processor 110 may estimate that the resolution of the original image is FHD of 1920×1080);
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to determining an input resolution of the content to be requested based on the display resolution and an upscaling factor based on the method of Kim’s reference. The suggestion / motivation would have been to provide quality upscaling performance in various streaming environments (See Kim, ¶ [0002–0006]).
However, Motilla and Kim fail(s) to teach selecting the upscaling model from a plurality of upscaling models to be used for upscaling the content based on the tile size and the upscaling factor, each upscaling model being trained with a particular tile size and a particular upscale factor for increasing the resolution of the content.
Guede, working in the same field of endeavor, teaches: selecting the upscaling model from a plurality of upscaling models to be used for upscaling the content based on the tile size and the upscaling factor (See Guede, ¶ [0178], According to this embodiment, the upscaling is performed using a neural network, …, For instance, one or more default CNN models are stored in memory, each default CNN models being associated with a CNN input block size, and a scale factor, …, According to another embodiment, the CNN model is selected based on an input block size of the CNN. Note: Examiner is interpreting the CNN as the upscaling model and an upscaling model of a particular scale factor is chosen based on the block size. Therefore the upscaling model is chosen based on the tile size and upscaling factor.), each upscaling model being trained with a particular tile size and a particular upscale factor for increasing the resolution of the content (See Guede, ¶ [0178], For instance, one or more default CNN models are stored in memory, each default CNN models being associated with a CNN input block size, and a scale factor, ..., At 1409, a CNN model is selected based on the decoded CNN parameters, and the decoded occupancy map is upscaled at 1410 using the selected CNN model).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to selecting the upscaling model from a plurality of upscaling models to be used for upscaling the content based on the tile size and the upscaling factor, each upscaling model being trained with a particular tile size and a particular upscale factor for increasing the resolution of the content based on the method of Guede’s reference. The suggestion/motivation would have been to reduce the size of the models and accurately process tiles using specific models for specific scaling factors (See Guede, ¶ [0178]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Kim and Guede with Motilla to obtain the invention as specified in claim 1.
Regarding claim 2, Motilla in view of Kim further in view of Guede teaches the method of claim 1, wherein receiving the content comprises: transmitting a request to receive the content according to the input resolution (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display);
receiving the content in a compressed format (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display. Note: Encoded lower-resolution images are a compressed format); and
[decoding the compressed format of the content into macroblocks of the content, wherein each macroblock is a segment of the content in a decompressed format].
However, Motilla and Kim fail(s) to teach decoding the compressed format of the content into macroblocks of the content, wherein each macroblock is a segment of the content in a decompressed format.
Guede, working in the same field of endeavor, teaches: decoding the compressed format of the content into macroblocks of the content, wherein each macroblock is a segment of the content in a decompressed format (See Guede, ¶ [0117], In step 4300, a decoder OMDEC may decode encoded information to derive a decoded occupancy map DOM. ¶ [0118] According to an embodiment, the video decoder VDEC and/or OMDEC may be a HEVC-based decoder. Note: HEVC decoder is a decoder that processes a single frame into segments of the frame for decoding which the examiner is interpreting as macroblocks).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to decoding the compressed format of the content into macroblocks of the content, wherein each macroblock is a segment of the content in a decompressed format based on the method of Guede’s reference. The suggestion/motivation would have been to reduce the size of the models and accurately process tiles using specific models for specific scaling factors (See Guede, ¶ [0178]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Guede with Motilla and Kim to obtain the invention as specified in claim 2.
Regarding claim 3, Motilla teaches the method of claim 1, wherein converting the content to enhance the resolution of the content using the upscaling model (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display) comprises:
upon obtaining a row of tiles of the content, converting each tile of the row of tiles to upscale the corresponding tile using the upscaling model, each tile including a plurality of macroblocks (See Motilla, ¶ [0082], In some embodiments, for example when a user selects a particular game title to play e.g. in a cloud environment, the client can download or be provided with a corresponding upscaling (e.g. super resolution) manifest file. The manifest file preferably contains the relevant data required by the client to perform image upscaling for the incoming images or video frames of that specific game title sent to it by the server. ¶ [0083], The manifest file sent to the client from the server may include information such as: ¶ [0084] Number of columns in a tile grid ¶ [0085] Number of rows in the tile grid ¶ [0086] List of super resolution model URLs to be downloaded by the client - an index represents an index present in a tile map 200 that can be supplied by the server, (see Server assisted metadata above)).
Regarding claim 4, Motilla teaches the method of claim 3, further comprising storing row data of the row of tiles of the content in a memory to be used by the upscaling model to process each tile of the row of tiles (See Motilla, ¶ [0082], In some embodiments, for example when a user selects a particular game title to play e.g. in a cloud environment, the client can download or be provided with a corresponding upscaling (e.g. super resolution) manifest file. The manifest file preferably contains the relevant data required by the client to perform image upscaling for the incoming images or video frames of that specific game title sent to it by the server. ¶ [0083], The manifest file sent to the client from the server may include information such as: ¶ [0084] Number of columns in a tile grid ¶ [0085] Number of rows in the tile grid ¶ [0086] List of super resolution model URLs to be downloaded by the client - an index represents an index present in a tile map 200 that can be supplied by the server, (see Server assisted metadata above)).
Regarding claim 5, Motilla teaches the method of claim 4, wherein the upscaling model is configured to clarify, sharpen, and upscale the content without losing information and characteristics of the content (See Motilla, ¶ [0052], A plurality of upscaling processes may be available to the client device. An upscaling process in some embodiments uses super resolution. Super resolution uses machine learning to clarify, sharpen and upscale the image without losing content and characteristics of the image).
Regarding claim 6, Motilla teaches the method of claim 1, wherein determining the tile size of the tile of the content to be processed by the upscaling model (See Motilla, ¶ [0048], The image data received at the client device is divided, or split, into image portions. Image portions may also be referred to herein as tiles) comprises:
determining the tile size of the tile of the content by considering an optimal balance between performance of the upscaling model and the memory and latency consumptions based on parameters (See Motilla, ¶ [0047], Handling and processing of larger tiles requires more powerful processors and more memory. Smaller tiles may lack contextual information required to produce a high-quality filling result. A tile size and shape are therefore chosen according to the hardware constraints. ¶ [0127], Depending on its capabilities the client device can perform additional optimizations during tile processing. For example, connected tiles can be merged into a single larger tile for processing if this is more efficient. The client can perform an initial calibration process to find the best tile sizes (using the per-tile overhead and the cost of the resolution processing)).
Regarding claim 11, claim 11 is rejected the same as claim 1 and the arguments similar to that presented above for claim 1 are equally applicable to the claim 11, and all of the other limitations similar to claim 1 are not repeated herein, but incorporated by reference. Furthermore, Motilla teaches a computing device for upscaling a content using an upscaling model, the computing device comprising: a processor; and a memory having a plurality of instructions stored thereon that, when executed by the processor, causes the computing device to (See Motilla, [FIG. 7], 702 Processor, 704 Main Memory).
Regarding claim 12, claim 12 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to the claim 12, and all of the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
Regarding claim 13, claim 13 is rejected the same as claim 3 and the arguments similar to that presented above for claim 3 are equally applicable to the claim 13, and all of the other limitations similar to claim 3 are not repeated herein, but incorporated by reference.
Regarding claim 14, claim 14 is rejected the same as claim 4 and the arguments similar to that presented above for claim 4 are equally applicable to the claim 14, and all of the other limitations similar to claim 4 are not repeated herein, but incorporated by reference.
Regarding claim 15, claim 15 is rejected the same as claim 5 and the arguments similar to that presented above for claim 5 are equally applicable to the claim 15, and all of the other limitations similar to claim 5 are not repeated herein, but incorporated by reference.
Regarding claim 16, claim 16 is rejected the same as claim 6 and the arguments similar to that presented above for claim 6 are equally applicable to the claim 16, and all of the other limitations similar to claim 6 are not repeated herein, but incorporated by reference.
Regarding claim 18, claim 18 is rejected the same as claim 1 and the arguments similar to that presented above for claim 1 are equally applicable to the claim 18, and all of the other limitations similar to claim 1 are not repeated herein, but incorporated by reference. Furthermore, Motilla teaches a computer-readable storage medium storing instructions for upscaling a content using an upscaling model, the instructions when executed by one or more processors of a computing device, cause the computing device to (See Motilla, [FIG. 7], 702 Processor, 704 Main Memory).
Regarding claim 19, claim 19 is rejected the same as claim 2 and the arguments similar to that presented above for claim 2 are equally applicable to the claim 19, and all of the other limitations similar to claim 2 are not repeated herein, but incorporated by reference.
Claim(s) 8, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Motilla et al. (US 20230325977 A1, hereafter, "Motilla") in view of Kim et al. (US 20210166304 A1, hereafter, “Kim) further in view of Guede et al. (US 20230377204 A1, hereafter, "Guede") further in view of Yuan et al. (US 20090324079 A1, hereafter, "Yuan").
Regarding claim 8, Motilla in view of Kim further in view of Guede teaches the method of claim 1, [wherein the tile has a shape of an elongated rectangle, and a width of the tile is greater than a height of the tile].
However, Motilla, Kim and Guede fail(s) to teach wherein the tile has a shape of an elongated rectangle, and a width of the tile is greater than a height of the tile.
Yuan, working in the same field of endeavor, teaches: wherein the tile has a shape of an elongated rectangle, and a width of the tile is greater than a height of the tile (See Yuan, ¶ [0047], Each patch (exemplary patches shown 81, 82, 83, 84, 85) may be an image region sampled around a center pixel (two exemplary patch centers shown in FIG. 786, 87). In some embodiments of the present invention, an image patch may be an 80-pixel by 30-pixel rectangle).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to wherein the tile has a shape of an elongated rectangle, and a width of the tile is greater than a height of the tile based on the method of Yuan’s reference. The suggestion/motivation would have been to reduce visible artefacts in the image and selectively process a specific region (See Yuan, ¶ [0002–0005]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Yuan with Motilla, Kim and Guede to obtain the invention as specified in claim 8.
Regarding claim 17, claim 17 is rejected the same as claim 8 and the arguments similar to that presented above for claim 8 are equally applicable to the claim 17, and all of the other limitations similar to claim 8 are not repeated herein, but incorporated by reference.
Regarding claim 20, Motilla in view of Kim further in view of Guede the computer-readable storage medium of claim 18, wherein to determine the tile size of the tile of the content to be processed by the upscaling model (See Motilla, ¶ [0047], Handling and processing of larger tiles requires more powerful processors and more memory. Smaller tiles may lack contextual information required to produce a high-quality filling result. A tile size and shape are therefore chosen according to the hardware constraints. ¶ [0127], Depending on its capabilities the client device can perform additional optimizations during tile processing. For example, connected tiles can be merged into a single larger tile for processing if this is more efficient. The client can perform an initial calibration process to find the best tile sizes (using the per-tile overhead and the cost of the resolution processing)) comprises to:
determine the tile size of the tile of the content by considering an optimal balance between performance of the upscaling model and the memory and latency consumptions based on parameters (See Motilla, ¶ [0047], Handling and processing of larger tiles requires more powerful processors and more memory. Smaller tiles may lack contextual information required to produce a high-quality filling result. A tile size and shape are therefore chosen according to the hardware constraints. ¶ [0127], Depending on its capabilities the client device can perform additional optimizations during tile processing. For example, connected tiles can be merged into a single larger tile for processing if this is more efficient. The client can perform an initial calibration process to find the best tile sizes (using the per-tile overhead and the cost of the resolution processing)), [wherein the tile has a shape of an elongated rectangle].
However, Motilla, Kim and Guede fail(s) to teach wherein the tile has a shape of an elongated rectangle.
Yuan, working in the same field of endeavor, teaches: wherein the tile has a shape of an elongated rectangle (See Yuan, ¶ [0047], Each patch (exemplary patches shown 81, 82, 83, 84, 85) may be an image region sampled around a center pixel (two exemplary patch centers shown in FIG. 786, 87). In some embodiments of the present invention, an image patch may be an 80-pixel by 30-pixel rectangle).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to wherein the tile has a shape of an elongated rectangle based on the method of Yuan’s reference. The suggestion/motivation would have been to reduce visible artefacts in the image and selectively process a specific region (See Yuan, ¶ [0002–0005]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Yuan with Motilla, Kim and Guede to obtain the invention as specified in claim 8.
Claim(s) 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Motilla et al. (US 20230325977 A1, hereafter, "Motilla") in view of Kim et al. (US 20210166304 A1, hereafter, “Kim) further in view of Guede et al. (US 20230377204 A1, hereafter, "Guede") further in view of Jeffrey et al. (US 20070040838 A1, hereafter, "Jeffrey").
Regarding claim 9, Motilla in view of Kim further in view of Guede teaches the method of claim 1, wherein determining the output display resolution of the visual display (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display. Note: the native resolution must be known to make the image suitable for the client display) comprises:
[in response to detecting the visual display, automatically selecting the highest available resolution of visual display as the display resolution].
However, Motilla, Kim and Guede fail(s) to teach in response to detecting the visual display, automatically selecting the highest available resolution of visual display as the display resolution.
Jeffrey, working in the same field of endeavor, teaches: in response to detecting the visual display, automatically selecting the highest available resolution of visual display as the display resolution (See Jeffrey, ¶ [0021], The host in a graphics display system may calculate and write the scale factor(s) to the graphics controller when it is desired to scale an image. To calculate the scale factor(s) for storing an image in the memory, the host must determine the image size (pq), and the memory size (mn). To calculate the scale factor(s) for writing an image stored in the memory to the display device, the host must determine at least the image size (pq), which is the memory size (mn), and the display resolution or size (xy)).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to in response to detecting the visual display, automatically selecting the highest available resolution of visual display as the display resolution based on the method of Jeffrey’s reference. The suggestion/motivation would have been to minimize the size of the memory, which reduces cost and also reduces power requirements (See Jeffrey, ¶ [0002–0008]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Jeffrey with Motilla, Kim and Guede to obtain the invention as specified in claim 9.
Regarding claim 10, Motilla in view of Kim further in view of Guede teaches the method of claim 1, wherein determining the output display resolution of the visual display (See Motilla, ¶ [0006], Images received at a client device from a server device, which may be transmitted as encoded lower-resolution images, often require processing such as video upscaling to achieve the intended higher-resolution image suitable for the native resolution of the client display. Note: the native resolution must be known to make the image suitable for the client display) comprises:
[receiving an input indicative of the output display resolution].
However, Motilla, Kim and Guede fail(s) to teach receiving an input indicative of the output display resolution.
Jeffrey, working in the same field of endeavor, teaches: receiving an input indicative of the output display resolution (See Jeffrey, ¶ [0024], The host may determine the display resolution (xy) by issuing a query to the display device).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify Motilla’s reference to receiving an input indicative of the output display resolution based on the method of Jeffrey’s reference. The suggestion/motivation would have been to minimize the size of the memory, which reduces cost and also reduces power requirements (See Jeffrey, ¶ [0002–0008]).
Further, one skilled in the art could have combined the elements as described above by known method with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Therefore, it would have been obvious to combine Jeffrey with Motilla, Kim and Guede to obtain the invention as specified in claim 10.
Allowable Subject Matter
Claim(s) 7 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.
Claim(s) 7 contain subject matter that is not disclosed or made obvious in the cited art.
In regard to claim 7, when considering claim 7 as a whole, prior art of record fails to disclose or render obvious, alone or in combination:
“wherein the parameters include a size of a decoder output macroblock, an input frame resolution, a session configuration, performance of the upscaling model, system limitations, and memory and latency requirements”.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Han et al. (US 20220368965 A1) teaches the present disclosure in some embodiments provides a system for and a method of providing a live video in real-time by transmitting the live video and patches which are a fraction of a frame of the live video by allocating and using bandwidth for transmitting the live video and bandwidth for transmitting the patches, respectively, and by subjecting, based on the patches, a deep neural network-based super-resolution model to online learning and thereby super-resolution processing the live video into a super-resolution live video.
Zhu et al. (US 11252300 B2) teaches training and upscaling a large-sized input image, including: dividing the large-sized input image into a plurality of small-sized sub-pictures; expanding each sub-picture of the plurality of small-sized sub-pictures using target padding pixels to produce an expanded sub-picture; upscaling each sub-picture using an ML-based upscaler to produce an expanded upscaled sub-picture; cropping the expanded upscaled sub-picture to an upscaled size equal to an original size of each sub-picture multiplied by an upscaling factor; repeating expanding, upscaling, and cropping for the plurality of sub-pictures; and concatenating the plurality of cropped sub-pictures to produce an output image.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DION J SATCHER whose telephone number is (703)756-5849. The examiner can normally be reached Monday - Thursday 5:30 am - 2:30 pm, Friday 5:30 am - 9:30 am PST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Henok Shiferaw can be reached at (571) 272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DION J SATCHER/Patent Examiner, Art Unit 2676
/Henok Shiferaw/Supervisory Patent Examiner, Art Unit 2676