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 .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 6-10, 12, 14 and 18-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Wang et al. (U.S. 2020/0327702), hereinafter Wang.
Regarding claims 1 and 19, Wang discloses an apparatus for processing video data comprising a processor and a non-transitory memory with instructions thereon, wherein the instructions upon execution by the processor (Wang [0018]), cause the processor to:
apply a super resolution (SR) process to a video unit at a level of an SR unit (Wang figs. 2 and 4), wherein the SR unit level includes more than one pixel of the video unit (Wang [0027] and [0045]); and
perform a conversion between a video comprising the video unit and a bitstream of the video based on the SR process as applied (Wang fig. 1),
wherein the SR unit changes from one level to another level within a sequence of frames or pictures depending on content of the video data (Wang [0007], [0009], figs. 2 and 4).
Regarding claim 6, Wang discloses the method of claim 1, wherein the SR process uses a neural network (NN) with the SR unit, or a region of the video unit that contains the SR unit as well as other pixels of the video unit as one of its inputs (Wang [0022] and [0001]).
Regarding claim 7, Wang discloses the method of claim 1, wherein the SR unit used for the SR process is included in the bitstream or pre-defined prior to the SR process being applied to the video unit (Wang figs. 1, 2 and 4).
Regarding claim 8, Wang discloses the method of claim 1, wherein the SR process applied to a first SR unit is different from the SR process applied to a second SR unit (Wang figs. 2 and 4).
Regarding claim 9, Wang discloses the method of claim 8, wherein the SR process applied to the first SR unit comprises one of a neural network (NN)-based SR process and a non-NN-based SR process, and wherein the SR process applied to the second SR unit comprises the other one of the NN based SR process and the non-NN-based SR process (Wang fig. 2 and [0023]).
Regarding claim 10, Wang discloses the method of claim 1, wherein an input of the SR process is at least one of a plurality of video unit levels, including a sequence of pictures level, a picture level, a slice level, a tile level, a brick level, a subpicture level, one or more coding tree units (CTUs) level, a CTU row level, one or more coding units (CUs) level, one or more coding tree blocks (CTBs) level, or a region level, wherein the input of the SR process at the region level covers more than one pixel (Wang [0009] and fig. 4).
Regarding claim 12, Wang discloses the method of claim 1, wherein the SR process comprises a convolutional neural network (CNN) SR process trained on frame-level data, and wherein the CNN SR process is used to up-sample an input at a frame-level or at a coding tree unit (CTU)-level (Wang [0022] and [0001]).
Regarding claim 14, Wang discloses the method of claim 1, wherein at least one of a down-sampling ratio of the video unit, encoded information of the video unit, and decoded information of the video unit is used as an input of the SR process, and wherein the encoded information, the decoded information, or both comprise one or more of a prediction signal, a partition structure, and an intra prediction mode of the video unit (Wang figs. 1, 2 and 4).
Regarding claim 18, Wang discloses the method of claim 1, wherein the conversion includes decoding the video data from the bitstream (Wang fig. 1).
Regarding claim 20, Wang discloses a non-transitory computer-readable storage medium storing instructions that cause a processor to (Wang [0018] and [0084]): apply a super resolution (SR) process to a video unit at a level of an SR unit, wherein the SR unit level includes more than one pixel of the video unit; and perform a conversion between a video comprising the video unit and a bitstream of the video based on the SR process as applied, wherein the SR unit changes from one level to another level within a sequence of frames or pictures depending on content of the video data (see claim 1).
Claim Rejections - 35 USC § 103
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 nonobviousness.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Da Silva Pratas Gabriel et al. (U.S. 2021/0211643), hereinafter Da Silva.
Regarding claim 2, Wang discloses the method of claim 1. Wang does not explicitly disclose wherein the SR unit used for the SR process and a video unit used for down-sampling are at the same level.
However, Da Silva teaches, wherein the SR unit used for the SR process and a video unit used for down-sampling are at the same level (Da Silva [0084] and [0142]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Da Silva to efficiently code high-resolution video frames (Da Silva [0065]).
Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Machii et al. (U.S. 2021/0327028), hereinafter Machii.
Regarding claim 3, Wang discloses the method of claim 1. Wang does not explicitly disclose wherein the SR unit used for the SR process and a video unit used for down-sampling are at different levels.
However, Machii teaches, wherein the SR unit used for the SR process and a video unit used for down-sampling are at different levels (Machii [0074]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Machii to be able to generate a super resolution imaged having a predetermined resolution based on image features (Machii [0074]).
Regarding claim 4, Wang in view of Machii teaches the method of claim 3, wherein the SR unit used for the SR process comprises a block or a coding tree unit (CTU) (Wang fig. 2), and wherein the method further comprises performing down-sampling at a picture level, a slice level, or a tile level (Machii [0025]).
The same motivation for claim 3 applies to claim 4.
Claim(s) 5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Machii as applied to claim 3 above, and further in view of Grois et al. (U.S. 2022/0103832), hereinafter Grois.
Regarding claim 5, Wang in view of Machii teaches the method of claim 3, wherein the SR unit used for the SR process comprises a coding tree unit (CTU) row, multiple CTUs, or multiple coding tree blocks (CTBs) (Wang [0052] and fig. 4).
Wang does not explicitly disclose wherein the method further comprises performing down-sampling at a CTU level or a CTB level.
However, Grois teaches wherein the method further comprises performing down-sampling at a CTU level or a CTB level (Grois [0079] and Abstract).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method taught by Wang in view of Machii with the missing limitations as taught by Grois to minimize cost of video coding without reducing visual presentation quality (Grois [0079] and Abstract).
Claim(s) 11 and 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Joshi et al. (U.S. 2019/0394482), hereinafter Joshi.
Regarding claim 11, Wang discloses the method of claim 10. Wang does not explicitly disclose wherein the input of the SR process is a coding tree block (CTB) that has been down-sampled or a frame that has been down-sampled.
However, Joshi teaches, wherein the input of the SR process is a coding tree block (CTB) that has been down-sampled or a frame that has been down-sampled (Joshi [0049]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Joshi to improve visual quality at low-bitrate settings (Joshi [0020]).
Regarding claim 17, Wang in view of Joshi teaches the method of claim 1, wherein the conversion includes encoding the video data into the bitstream (Joshi [0061]).
The same motivation for claim 11 applies to claim 17.
Claim(s) 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Ratner et al. (U.S. 2017/0337711), hereinafter Ratner.
Regarding claim 13, Wang discloses the method of claim 1. Wang does not explicitly disclose wherein the SR process comprises a convolutional neural network (CNN) SR process trained on coding tree unit (CTU)-level data, and wherein the CNN SR process is used to up-sample an input at a frame-level or at a coding tree unit (CTU)-level.
However, Ratner teaches, wherein the SR process comprises a convolutional neural network (CNN) SR process trained on coding tree unit (CTU)-level data, and wherein the CNN SR process is used to up-sample an input at a frame-level or at a coding tree unit (CTU)-level (Ratner [0518]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Ratner to compress or encode video data with greater efficiency and quality (Ratner [0002]).
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Meardi et al. (U.S. 2024/0040160), hereinafter Meardi.
Regarding claim 15, Wang in discloses the method of claim 14. Wang does not explicitly disclose wherein the SR process comprises a convolutional neural network (CNN) SR process, and wherein a stride of a convolutional layer of the CNN SR process is dependent on the down-sampling ratio of an input of the CNN SR process.
However, Meardi teaches, wherein the SR process comprises a convolutional neural network (CNN) SR process, and wherein a stride of a convolutional layer of the CNN SR process is dependent on the down-sampling ratio of an input of the CNN SR process (Meardi [0150]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Meardi to achieve downsampling with an efficient light-weight neural network architecture (Meardi [0150]).
Claim(s) 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Yea et al. (U.S. 2022/0201307), hereinafter Yea.
Regarding claim 16, Wang discloses the method of claim 14. Wang does not explicitly disclose wherein a horizontal down-sampling ratio and a vertical down-sampling ratio are the same or different.
However, Yea teaches, wherein a horizontal down-sampling ratio and a vertical down-sampling ratio are the same or different (Yea [0150]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Wang’s method with the missing limitations as taught by Yea to achieve super resolution by applying down sampling in one direction (Yea [0150]).
Response to Arguments
Applicant's arguments filed 12/29/25 in regards to the previously presented portions of the claims have been fully considered but they are not persuasive.
On pgs. 9-11 of the Applicant’s Response, the Applicant argues that Wang does not disclose the last 2 lines of claim 1.
The Examiner respectfully disagrees. Under the broadest reasonable interpretation of the current claim language of claim 1, Wang discloses a selective application of multiple SR unit levels such as a block level which is used for low quantization parameter frames and a frame level which is used for I-frames (Wang [0007], [0009], figs. 2 and 4). This is a change in level depending on the content of the video data because a low quantization parameter frame is not the same content of video data as an I-frame. Therefore, Wang discloses the previously presented limitations of claim 1 as cited above.
A new grounds of rejection was added for the change in scope of claim 20 to overcome the non-functional descriptive material issue.
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.
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/MATTHEW K KWAN/Primary Examiner, Art Unit 2482
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