Office Action Predictor
Last updated: April 15, 2026
Application No. 18/368,683

VIDEO PICTURE ENCODING AND DECODING METHOD AND RELATED DEVICE

Non-Final OA §103
Filed
Sep 15, 2023
Examiner
BILLAH, MASUM
Art Unit
2486
Tech Center
2400 — Computer Networks
Assignee
Huawei Technologies Co., LTD.
OA Round
2 (Non-Final)
80%
Grant Probability
Favorable
2-3
OA Rounds
2y 6m
To Grant
91%
With Interview

Examiner Intelligence

Grants 80% — above average
80%
Career Allow Rate
335 granted / 419 resolved
+22.0% vs TC avg
Moderate +11% lift
Without
With
+10.7%
Interview Lift
resolved cases with interview
Typical timeline
2y 6m
Avg Prosecution
31 currently pending
Career history
450
Total Applications
across all art units

Statute-Specific Performance

§101
3.9%
-36.1% vs TC avg
§103
60.4%
+20.4% vs TC avg
§102
14.2%
-25.8% vs TC avg
§112
11.3%
-28.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 419 resolved cases

Office Action

§103
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 . DETAILED ACTION This Office Action is in response to the application 18/368,683,008 filed on 10/17/2025. In the instant Amendment, claims 8 – 11, 19, 21, 22 and 23 have been amended. Claim 26 and 29 has been cancelled. Claims 1 – 25, 27, 28 have been examined and are pending in this application. This action is made Non-Final. Information Disclosure Statement The information disclosure statement (IDS) submitted on 12/31/2024 and 09/25/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Response to Arguments Applicant’s arguments, see pages 13 - 17, filed on 10/17/2025, with respect to the rejection(s) of claim(s) 1 – 25 and 27 – 28 under pre-AIA 35 U.S.C. § 102(a)(1) have been fully considered and are persuasive. Therefore, the previous rejection mailed on 08/06/2025 has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of newly found prior art reference(s). The rejection of claims 1 – 25, 27 and 28 under 35 U.S.C. 112 (b) or 35 U.S.C. 112 (pre-AIA ), second paragraph as being indefinite has been withdrawn in view of Applicant’s responses. 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 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. Claim 1, 4 – 7, 12, 15 – 18, 24, 25, 27, 28 are rejected under 35 U.S.C. 103 as being unpatentable over Pfaff et al. (US 2021/0014531 A1). in view of Chen et al. (US 2022/0014735 A1). Regarding claim 1, Pfaff discloses: “a video picture decoding method, comprising: receiving a bitstream of a current picture [see para: 0069; FIG. 1 shows an apparatus for block-wise encoding a picture 10 into a datastream 12. The apparatus is indicated using reference sign 14 and may be a still picture encoder or a video encoder]; performing a probability estimation on input data by using a neural network obtained through training, to obtain a probability distribution of residual values of a plurality of samples comprised in a residual of the current picture [see para: 0082; The specific example set out hereinafter, also provides encoder and decoder with another neural network 84 which is dedicated to provide a probability value for each neural network-based intra-prediction mode within set 72 on the basis of a set 86 of neighboring samples which may or may not coincide with set 60. The probability values thus provided when the neural network 84 assists in rendering the side information 70 for the mode selection more effective. For instance, in the example described below, it is assumed that a variable length code is used to point to one of the intra-prediction modes and at least as far as set 72 is concerned, the probability values provided by the neural network 84 enable to use the variable length code within the side information 70 as an index into an ordered list of intra-prediction modes ordered according to the probability values output by neural network 84 for the neural network-based intra-prediction modes within set 72, thereby optimizing or reducing the code rate for the side information 70], Pfaff does not explicitly disclose: “wherein the input data comprises at least a residual of a reference picture, and wherein the reference picture is a decoded picture obtained before the current picture is decoded; performing an arithmetic entropy decoding on the bitstream based on the probability distribution of the residual values of the plurality of samples comprised in the residual of the current picture, to obtain first entropy decoding data, wherein the first entropy decoding data represents the residual of the current picture; and obtaining a reconstructed sample value of the current picture based on the residual of the current picture”. However, Chen, from the same or similar field of endeavor teaches: “wherein the input data comprises at least a residual of a reference picture, and wherein the reference picture is a decoded picture obtained before the current picture is decoded [see para: 0087; Residual data represents pixel differences between the original block to be coded and the predictive block. An inter-coded block is encoded according to a motion vector that points to a block of reference samples forming the predictive block, and the residual data indicating the difference between the coded block and the predictive block. An intra-coded block is encoded according to an intra-coding mode and the residual data. For further compression, the residual data may be transformed from the pixel domain to a transform domain, resulting in residual transform coefficients, which then may be quantized]; performing an arithmetic entropy decoding on the bitstream based on the probability distribution of the residual values of the plurality of samples [see para: 0161; During the decoding process, video decoder 30 receives an encoded video bitstream that represents video blocks of an encoded video slice and associated syntax elements from video encoder 20. Entropy decoding unit 70 of the video decoder 30 entropy decodes the bitstream to generate quantized coefficients, motion vectors or intra-prediction mode indicators, and other syntax elements. Entropy decoding unit 70 forwards the motion vectors and other syntax elements to motion compensation unit 72. Video decoder 30 may receive the syntax elements at the video slice level and/or the video block level] comprised in the residual of the current picture, to obtain first entropy decoding data, wherein the first entropy decoding data represents the residual of the current picture [see para: 0087; Residual data represents pixel differences between the original block to be coded and the predictive block. An inter-coded block is encoded according to a motion vector that points to a block of reference samples forming the predictive block, and the residual data indicating the difference between the coded block and the predictive block. An intra-coded block is encoded according to an intra-coding mode and the residual data. For further compression, the residual data may be transformed from the pixel domain to a transform domain, resulting in residual transform coefficients, which then may be quantized]; and obtaining a reconstructed sample value of the current picture based on the residual of the current picture [see para: 0078; Motion compensation unit 44 may calculate a reference block by adding the residual block to a predictive block of one of the frames of reference frame memory 64. Motion compensation unit 44 may also apply one or more interpolation filters to the reconstructed residual block to calculate sub-integer pixel values for use in motion estimation. Summer 62 adds the reconstructed residual block to the motion compensated prediction block produced by motion compensation unit 44 to produce a reconstructed video block for storage in reference frame memory 64. The reconstructed video block may be used by motion estimation unit 42 and motion compensation unit 44 as a reference block to inter-code a block in a subsequent video frame]. It would have been obvious to the person of ordinary skill in the art before the effective filing date of the claimed invention to modify the block-wise decoding a picture from a data stream system disclosed by Pfaff to add the teachings of Chen as above, in order to determine residual reference picture, residual data calculated by the differences between the original block to be coded and the predictive block and perform an arithmetic entropy decoding on the bitstream based on the probability distribution of the residual values of the samples and obtain reconstructed sample value of the current picture based on the residual of the current picture [Chen see para: 0087; 0161; 0078]. Regarding claim 4, Pfaff and Chen disclose all the limitation of claim 1 and are analyzed as previously discussed with respect to that claim. Pfaff discloses: “the probability distribution represents probability distribution of residual values of all samples in a plurality of samples of the current picture; or the probability distribution represents the probability distribution of the residual values of the plurality of samples of the current picture[see para: 0161; FIG. 7d shows a further variant of FIG. 7a , namely the one according to which the index 70 b is coded using entropy coding and decoded from data stream 12 using entropy decoding, commonly denoted using reference sign 100. The sample statistics or the probability distribution used for the entropy coding 100 is controlled by the probability values output by neural network 84 as explained above, this renders the entropy coding of index 70 b very efficient]. Pfaff does not explicitly disclose: “wherein the probability distribution represents probability distribution of a plurality of differences between reconstructed values of the plurality of samples comprised in the residual of the current picture and predicted values of the plurality of samples”. However, Chen, from the same or similar field of endeavor teaches: “wherein the probability distribution represents probability distribution of a plurality of differences between reconstructed values of the plurality of samples comprised in the residual of the current picture and predicted values of the plurality of samples [see para: 0087; Spatial or temporal prediction results in a predictive block for a block to be coded. Residual data represents pixel differences between the original block to be coded and the predictive block. An inter-coded block is encoded according to a motion vector that points to a block of reference samples forming the predictive block, and the residual data indicating the difference between the coded block and the predictive block. An intra-coded block is encoded according to an intra-coding mode and the residual data. For further compression, the residual data may be transformed from the pixel domain to a transform domain, resulting in residual transform coefficients, which then may be quantized. The quantized transform coefficients, initially arranged in a two-dimensional array, may be scanned in order to produce a one-dimensional vector of transform coefficients, and entropy coding may be applied to achieve even more compression]; It would have been obvious to the person of ordinary skill in the art before the effective filing date of the claimed invention to modify the block-wise decoding a picture from a data stream system disclosed by Pfaff to add the teachings of Chen as above, in order to determine the difference of residual values to improve the probability distribution by calculating plurality of differences between reconstructed values of the plurality of samples between the original block to be coded and the predictive block [Chen see para: 0087]. Regarding claim 5, Pfaff and Chen disclose all the limitation of claim 1 and are analyzed as previously discussed with respect to that claim. Pfaff does not explicitly disclose: “wherein the first entropy decoding data is the residual of the current picture, or a feature map of the residual of the current picture, or a transformed and quantized residual of the current picture”. However, Chen, from the same or similar field of endeavor teaches: “wherein the first entropy decoding data is the residual of the current picture, or a feature map of the residual of the current picture, or a transformed and quantized residual of the current picture [see para: 0087; For further compression, the residual data may be transformed from the pixel domain to a transform domain, resulting in residual transform coefficients, which then may be quantized. The quantized transform coefficients, initially arranged in a two-dimensional array, may be scanned in order to produce a one-dimensional vector of transform coefficients, and entropy coding may be applied to achieve even more compression]. It would have been obvious to the person of ordinary skill in the art before the effective filing date of the claimed invention to modify the block-wise decoding a picture from a data stream system disclosed by Pfaff to add the teachings of Chen as above, in order to provide a means for improving entropy decoding data which is the residual value or the difference of the current picture and predicted block, or a feature map of the residual of the current picture, for example, one-dimensional vector of transform coefficients, and entropy coding may be applied to achieve more compression results [Chen see para: 0087]. Regarding claim 6, Pfaff and Chen disclose all the limitation of claim 5 and are analyzed as previously discussed with respect to that claim. Furthermore, Pfaff discloses: “wherein the first entropy decoding data is the feature map of the residual of the current picture, the method further comprising’s: obtaining the residual of the current picture based on the feature map of the residual of the current picture by using a decoder network [see para: 0169; A common feature of the examples of FIGS. 9a and 9b which is also used by some of the examples of FIGS. 7a to 7d was the fact that the probability values of the neural network values in order to improve or reduce the overhead associated with the side information 70 for signaling the mode determined on the encoder side at the optimization process 90 to the decoder. As indicated above with respect to the examples of FIGS. 7a to 7d , however, it should be clear that the examples of FIGS. 9a and 9b may be varied to the extent that no side information 70 is spent in datastream 12 with respect to the mode selection at all]. Regarding claim 7, Pfaff and Chen disclose all the limitation of claim 5 and are analyzed as previously discussed with respect to that claim. Pfaff does not explicitly disclose: “wherein the first entropy decoding data is the transformed and quantized residual of the current picture, performing inverse transformation and inverse quantization on the transformed and quantized residual of the current picture, to obtain the residual of the current picture”. However, Chen, from the same or similar field of endeavor teaches: “wherein the first entropy decoding data is the transformed and quantized residual of the current picture, performing inverse transformation and inverse quantization on the transformed and quantized residual of the current picture, to obtain the residual of the current picture [see para: 0062; For video block reconstruction, video encoder 20 also includes inverse quantization unit 58, inverse transform unit 60, and summer 62. A deblocking filter (not shown in FIG. 2) may also be included to filter block boundaries to remove blockiness artifacts from reconstructed video. If desired, the deblocking filter would typically filter the output of summer 62. Additional filters (in loop or post loop) may also be used in addition to the deblocking filter. Such filters are not shown for brevity, but if desired, may filter the output of summer 50 (as an in-loop filter)]. It would have been obvious to the person of ordinary skill in the art before the effective filing date of the claimed invention to modify the block-wise decoding a picture from a data stream system disclosed by Pfaff to add the teachings of Chen as above, in order to provide a means for improving performing inverse transformation and inverse quantization on the transformed and quantized residual of the current picture to obtain the residual of the current picture, as described in the above para, video encoder also includes inverse quantization unit, inverse transform unit to determine the difference value of the current picture and to be coded block [Chen see para: 0062]. Regarding claim 12, 24, 25, 27, 28, claim 12, 24, 25, 27, 28 is rejected under the same art and evidentiary limitations as determined for the method of claim 1. Regarding claim 15, claim 15 is rejected under the same art and evidentiary limitations as determined for the method of claim 4. Regarding claim 16, claim 16 is rejected under the same art and evidentiary limitations as determined for the method of claim 5. Regarding claim 17, claim 17 is rejected under the same art and evidentiary limitations as determined for the method of claim 6. Regarding claim 18, claim 18 is rejected under the same art and evidentiary limitations as determined for the method of claim 7. Allowable Subject Matter Claims 2, 3, 8 – 11, 13, 14, 19, 20 – 23 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 The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Galpin et al (US 11,323,716 B2). Any inquiry concerning this communication or earlier communications from the examiner should be directed to Masum Billah whose telephone number is (571)270-0701. The examiner can normally be reached Mon - Friday 9 - 5 PM ET. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jamie J. Atala can be reached at (571) 272-7384. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /MASUM BILLAH/Primary Patent Examiner, Art Unit 2486
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Prosecution Timeline

Sep 15, 2023
Application Filed
Oct 31, 2023
Response after Non-Final Action
Jul 26, 2025
Non-Final Rejection — §103
Oct 17, 2025
Response Filed
Jan 21, 2026
Non-Final Rejection — §103
Mar 27, 2026
Response Filed

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

2-3
Expected OA Rounds
80%
Grant Probability
91%
With Interview (+10.7%)
2y 6m
Median Time to Grant
Moderate
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