DETAILED ACTION
1. 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 § 101
2. 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.
Claim 20 is rejected under 35 U.S.C. § 101 because the claim invention is not supported by a process, machine, manufacture, or composition of matter. In the state of the art, transitory signals are commonplace as a medium for transmitting computer instructions and thus, in the absence of any evidence to the contrary and given a broadest reasonable interpretation, the scope of a "computer readable medium" covers a signal per se. A transitory signal does not fall within the definition of a process, machine, manufacture, or composition of matters. Independent claim 13 when read in light of specification “the storage (770) may be removable or non-removable, and includes magnetic media (such as magnetic disks, magnetic tapes or cassettes), optical disk media and/or any other media which can be used to store information” (Specification paragraph 0181) does not define a computer-readable medium to include the disclosed tangible computer readable medium, while at the same time excluding the intangible media such as signals, carrier waves, propagated signals, etc, and is thus non-statutory for that reason.. The specification or claims must be amended to limit the computer-readable medium to only non-transitory signals, and state the exclusion of transitory signals (See Official Gazette Notice 1351 OG 212, dated February 23, 2010). The Examiner suggests amending the claims to state "A non-transitory computer-readable media…" to overcome the rejection under 35 U.S.C. § 101.
Claim Rejections - 35 USC §103
3. 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.
Claims 1-10, 13-16, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al (Pub. No.: US 2020/0327702 A1; hereinafter Wang) in view of KIM et al (Pub. No.: US 2023/0102895 A1; hereinafter KIM)
Consider claims 1, 9, and 15, Wang clearly shows and discloses a method, a client computing device, a one or more computer-readable media having stored therein computer-executable instructions for causing a processor system, when programmed thereby, to perform operations comprising: receiving encoded data in a bitstream for a current unit of a video sequence (system 100 receives an input video bitstream 111 (representative of video at a lower resolution) for super-resolution processing and system 100 provides upsampling to output video 118 at a higher resolution) (fig. 1, label 111, paragraphs: 0025, 0104); decoding the encoded data, thereby producing decoded video for the current unit of the video sequence (Video decoder 101 receives input video bitstream 111 and decodes input video bitstream 111 (by implementing the corresponding codec) to generate decoded video as video frames 113, video decoder 101 generates the metadata including QPs and video coding modes) (fig. 1, label: 101; paragraphs: 0027, and 0028); determining whether or not to perform post-processing based at least in part on results of video quality analysis (Fig. 1, QP comparison module 102 (QP<TH), The threshold may be any suitable value to indicate high compression (e.g., low QP) versus low compression (e.g., high QP) thus the QP gives an indication of video quality; Fig. 1 AI Based Super Resolution 106 which is applies only for a QP<TH (step 102) and Residuals not equal to zero; Fig. 6, QP comparison 603 (QP<TH) ) (fig. 1, label 102, fig. 6, label 603, paragraphs: 0030 and 0060); and responsive to determining to perform post-processing, applying a trained post-processing model to at least some of decoded video for the video sequence (where second video enhancement processing is applied such that the second video enhancement processing employs a deep learning network) (fig. 1, label 106, fig.6, label: 607, paragraphs: 0035 and 0064); however, Wang does not specifically disclose another example for decoding the encoded data, thereby producing decoded video for the current unit of the video sequence.
In the same field of endeavor, KIM clearly specifically disclose another example for decoding the encoded data, thereby producing decoded video for the current unit of the video sequence (paragraphs: 0004, 0181, fig. 2, image processing module/decoder fig. 9, label 901).
Therefore, it would have been obvious to a person of ordinary skill in the art at the time the invention was made to incorporate the teaching of KIM into teaching of Wang for the purpose of using another example for producing decoded video data.
Consider claim 2, Wang and KIM clearly show the client computing device, wherein the video quality analysis uses a machine learning model with a long short-term memory (“LSTM”) network (KIM: paragraphs: 0085, and 0037).
Consider claim 3, Wang and KIM clearly show the client computing device, wherein the operations further comprise: determining whether or not to analyze video quality; and responsive to determining to analyze video quality, performing the video quality analysis on the decoded video for the current unit of the video sequence (KIM: paragraphs: 0029, and 0157-0160).
Consider claim 4, Wang and KIM clearly show the client computing device, wherein the determining whether or not to perform post-processing depends on results of the video quality analysis on the decoded video for the current unit of the video sequence (KIM: fig. 9, label 903).
Consider claim 5, Wang and KIM clearly show the client computing device, wherein the determining whether or not to perform post-processing includes comparing the results of the video quality analysis on the decoded video for the current unit of the video sequence to a video quality threshold (KIM: paragraphs: 0080 and fig. 9, label 907).
Consider claim 6, Wang and KIM clearly show the client computing device, wherein the trained post-processing model is a video restoration model configured to mitigate compression artifacts (KIM: paragraphs: 0182, fig. 9, label 903).
Consider claim 7, Wang and KIM clearly show the client computing device, wherein the operations further comprise: receiving, from a server computing device, the results of the video quality analysis (KIM: paragraphs: 0064 and 0069 and fig. 8).
Consider claim 8 Wang and KIM clearly show the client computing device, wherein the determining whether or not to perform post-processing depends on results of the video quality analysis on decoded video for a previous unit of the video sequence (KIM: paragraphs:).
Consider claim 9, Wang and KIM clearly show the client computing device, wherein the determining whether or not to perform post-processing includes comparing the results of the video quality analysis on the decoded video for the previous unit of the video sequence to a video quality threshold (Wang: fig. 2 and KIM: fig. 9).
Consider claim 10, Wang and KIM clearly show the client computing device, wherein the trained post-processing model is: a super-resolution/video restoration model configured to increase spatial resolution, mitigate compression artifacts, and mitigate sampling artifacts; or a video restoration model configured to mitigate compression artifacts (KIM: paragraphs: 0177, 0188, 0209).
Consider claim 13, Wang and KIM clearly show the client computing device, wherein the current unit of the video sequence is a slice or frame (Wang: paragraphs:0027).
Consider claim 14, Wang and KIM clearly show the client computing device, wherein the trained post-processing model is configured to perform post-processing of video for a given video codec, a given profile for the given video codec, and a range of spatial resolutions (Wang: paragraphs: 0038).
Consider claim 15, Wang and KIM clearly show the client computing device, wherein the operations further comprise, for each of multiple subsequent units of the video sequence: repeating the receiving, the decoding, the determining, and the applying the trained post-processing model for the subsequent unit of the video sequence (Wang: paragraphs: fig. 1, label 102, fig. 6, label 603, paragraphs: 0030 and 0060).
Consider claim 16, Wang and KIM clearly show the client computing device, wherein the operations further comprise: rendering video for display, the rendered video including results of the applying the trained post-processing model to the at least some of the decoded video for the video sequence (Wang: paragraphs: fig. 1, label 102, fig. 6, label 603, paragraphs: 0030 and 0060).
Allowable Subject Matter
Claims 11, 12, 17, and 18 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Amal Zenati whose telephone number is 571- 270- 1947. The examiner can normally be reached on 8:00 -5:00 M-F.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ahmad Matar can be reached on 571- 272- 7488. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300.
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/AMAL S ZENATI/Primary Examiner, Art Unit 2693
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