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’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged (US Provisional Application 63/668,683 filed July 8th, 2024).
Response to Arguments
Applicant amended claims 1, 3, 5 – 8, 10, 13 – 14, 16, and 19 – 20 beyond formalities and 112 Rejections.
Applicant cancelled claims 2, 4, 9, 11 – 12, 15, and 17 – 18.
Applicant added new claims 21 – 28.
The pending claims are 1, 3, 5 – 8, 10, 13 – 14, 16, and 19 – 28 [Page 7 line 19 – Page 8 line 4].
Applicant provided their summary of the previous Office Action [Page 7 lines 1 – 13] and their version of the Interview conducted on March 18th, 2026 [Page 7 lines 14 – 18].
Applicant amended the Specification to address Examiner’s Specification Objection [Page 8 lines 5 – 9].
Applicant amended the claims to address Examiner’s 112 Rejections [Page 8 lines 10 – 17]. The Examiner reconsiders the Rejections in view of the new and amended claims.
Applicant’s arguments with respect to claim(s) 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
First, the Applicant recites the references against the claims [Page 7 lines 1 – 13 and Page 8 lines 18 – 21].
Second, the Applicant recites amended independent claim 1 [Page 8 lines 22 – 29].
Third, the Applicant provides their summary is of Chen [Page 9 lines 1 – 9], Hasse [Page 9 lines 10 – 17], and Balcilar [Page 9 lines 18 – 24]. The Examiner notes at least in Balcilar Paragraphs 129 – 130 and 246 the “adjusting” feature is taught. Additionally claim 3 provides other types of adjustments that appear contrary than that argued, but selection of a context table is considered an adjustment as claimed in the independent claim. Further, there are no specific Specification examples beyond the mere recitation of the claim language to support other understanding of “adjusting” being argued.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., “adjusting the selected CDF”) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Fourth, the Applicant cites alleged benefits of the invention contending the current cited references do not render obvious features of the amended independent claims [Page 10 lines 1 – 11]. The Examiner disagrees for at least the reasons given above; however in the sole interest to expedite prosecution cites at least a new reference against the claims.
Fifth, the Applicant amended independent claim 16 to address Examiner’s 102 Rejection in view of Chen [Page 10 lines 12 – 21]. The Examiner reconsiders the Rejection in view of the amended claims. The Examiner as a courtesy notes there is antecedent basis issues with numerous “a bitstream” recitations.
Sixth, the Applicant concludes the claims are allowable for at least the reasons given [Page 10 lines 22 – 26].
While the Applicant’s points may be understood, the Examiner respectfully disagrees; however, in view of the amended claims a new reference is cited in the sole interest to expedite prosecution.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on December 19th, 2025 was filed before the mailing date of the First Action on the Merits (mailed January 9th, 2026). The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the Examiner.
Claim Objections
Claim 26 is objected to under 37 CFR 1.75 as being a substantial duplicate of claim 23. When two claims in an application are duplicates or else are so close in content that they both cover the same thing, despite a slight difference in wording, it is proper after allowing one claim to object to the other as being a substantial duplicate of the allowed claim. See MPEP § 608.01(m).
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.
Claim 25 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 25 recites the limitation "updated CDF" in line 2. There is insufficient antecedent basis for this limitation in the claim. The Examiner notes claim 22 which is similar to the recitation of claim 25 depends on claim 3 which introduces the features being claimed. No such dependency of introduction of the “updated CDF” is made as claim 10 only recites “adjusting” the CDF from which claim 25 depends.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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(s) 1, 3, 5 – 8, 10, 13 – 14, 16, and 19 – 28 are rejected under 35 U.S.C. 103 as being unpatentable over Chen, et al. (WO2023/177752 A1 referred to as “Chen” throughout) [First Cited in the Office Action mailed January 9th, 2026], and further in view of Hasse, et al. (US PG PUB 2023/0238982 A1 referred to as “Hasse” throughout), Balcilar, et al. (WO2025/149595 A1 referred to as “Balcilar” throughout in which citations will come from the WIPO Document in lieu of all enabling US Provisional Applications) [First Cited in the Office Action mailed January 9th, 2026], and Xiu, et al. (WO2024/227118 A1 referred to as “Xiu” throughout).
Examiner Note for all claims: Applicant in Specification Paragraph 19 renders obvious “a context (e.g. a CDF)” thus context models / tables are obvious variant of the claimed “CDF” (cumulative distribution function) which are probability values. Thus, the Examiner in citing context models / tables notes one of ordinary skill in the art in view of the Specification understands the obvious variants between the context tables / models cited and the claimed “CDF” or use of probabilities including states, values, or a table of probabilities.
Regarding claim 13, see claim 5 which recites the same / similar limitation and thus similar reasoning applies in view of at least Chen Paragraphs 54, 72, and 75 – 78 (encoding and decoding are faithful inverse processes with some common steps).
Regarding claim 14, see claim 8 which recites the same / similar limitation and thus similar reasoning applies in view of at least Chen Paragraphs 54, 72, and 75 – 78 (encoding and decoding are faithful inverse processes with some common steps).
Regarding claim 16, see claim 10 which is the apparatus performing the encoding method claimed and Chen Paragraph 202 (structures / computer with processor and memory storing the bitstream).
Regarding claim 19, see claim 13 which is the apparatus performing the encoding method claimed and Chen Paragraph 202 (structures / computer with processor and memory storing the bitstream).
Regarding claim 20, see claim 14 which is the apparatus performing the encoding method claimed and Chen Paragraph 202 (structures / computer with processor and memory storing the bitstream).
Regarding claim 24, see claim 21 which recites the same / similar limitation and thus similar reasoning applies in view of at least Chen Paragraphs 54, 72, and 75 – 78 (encoding and decoding are faithful inverse processes with some common steps).
Regarding claim 25, see claim 22 which recites the same / similar limitation and thus similar reasoning applies in view of at least Chen Paragraphs 54, 72, and 75 – 78 (encoding and decoding are faithful inverse processes with some common steps).
Regarding claim 26, see claim 23 which recites the same / similar limitation and thus similar reasoning applies in view of at least Chen Paragraphs 54, 72, and 75 – 78 (encoding and decoding are faithful inverse processes with some common steps).
Regarding claim 27, see claim 21 which is the apparatus performing the encoding method claimed and Chen Paragraph 202 (structures / computer with processor and memory storing the bitstream).
Regarding claim 28, see claim 23 which is the apparatus performing the encoding method claimed and Chen Paragraph 202 (structures / computer with processor and memory storing the bitstream).
Regarding claim 1, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
receiving a video bitstream comprising a plurality of blocks and a syntax element [Chen Figures 1 and 2 (subfigures included see at least reference character 30 (decoder – detailed in Figure 2A receiving the bitstream input in reference character 201) and a plurality of blocks in Figures 1D – 1F (see at least reference characters 400, 410, 420, 430, and 440) as well as Paragraphs 77 – 82 (bitstream formed in encoder with information on blocks and syntax to decode))];
selecting a cumulative distribution function (CDF) for the syntax element from a set of two or more CDFs, wherein the CDF is selected [Chen Paragraphs 136 – 139 ( selection of context models based on syntax elements / dependent quantizers in combination with Balcilar Figures 7 – 9 as well as Paragraphs 136 – 151 (including code snippets for selection of the table (e.g. Table 4) based on dependent quantizer state information)] based on whether a first scalar a state of a dependent quantizer or a second scalar quantizer is selected for dependent scalar quantization of transform coefficients corresponding to the plurality of blocks [Chen Figures 5 – 6 as well as Paragraphs 94 – 97 (syntax elements indicating quantized transform coefficients encoded and decoded), 106 – 109 (QP dependent parameter to initialize / adjust the context model to use) and 116 – 120 (signaling in a slice (or picture) header initialization information for the context table and if a dependent quantizer / quantization state is used); Balcilar Figure 8 as well as Paragraphs 130 – 136 (DQ performed on transform coefficients based on levels / quantization of the coefficients) and 152 – 160 (Table 5 included); Xiu Figures 5 – 7 as well as Paragraphs 94 – 100 (states of DQ based on transform coefficients)];
adjusting the CDF using one or more values based on whether the first scalar quantizer or the second scalar quantizer is selected [Chen Figures 8 – 9 as well as Paragraphs 106 – 109 (initialization based on parameters and quantizers), 114 – 121 (weights to adapt probabilities as functions of the quantization step size and parity state) and 180 – 188 in combination with Balcilar Paragraphs 129 – 130 (scalar quantizers) and 136 – 144 (quantization states Q0 and Q1 are used to adjust the CDF / context with dependent / scalar quantizers in Paragraphs 148 – 153) or Hasse Figure 3 as well as Paragraphs 80 – 83 (arithmetic / entropy decoding based on a dependent quantization), 133 – 140 (initialization of the context model based on the state of a dependent quantizer including Table 1), and 179 – 199 (adjusting / adapting the CDF / probability state of the context model); Xiu Figure 5 – 7 as well as Paragraphs 95 – 100 (context selection and updates to contexts based on the quantization state) and 131 – 132 (updating the context / weights to combine with Chen)];
decoding the syntax element using the adjusted CDF [Chen Figures 2 (subfigures included and in particularly reference character 201 and 202) and 5 – 6 as well as Paragraphs 78 – 82 (decoding syntax elements), 105 – 107 (context model / probability used to decode the syntax elements), and 116 – 120 and 135 – 138 (signaling initialization of the context model / table to use and if the information is in a bock of CTU thus the block is decoded based on signaling syntax elements)]; and
decoding at least one block of the plurality of blocks based on the syntax element [Chen Figures 2 (subfigures included and in particularly reference character 201 and 202) and 5 – 6 as well as Paragraphs 78 – 82 (decoding syntax elements), 105 – 107 (context model / probability used to decode the syntax elements), and 116 – 120 (initialization syntax – combinable with Balcilar) and 135 – 138 (signaling initialization of the context model / table to use and if the information is in a bock of CTU thus the block is decoded based on signaling syntax elements); Balcilar Figures 7 – 8 as well as Paragraphs 136 – 143 (transmitting the context model and decoding syntax elements / information from the syntax elements with the context model / probability information) 146 – 150 (enabling dependent quantizers on a picture level to modify / combine with Chen)].
The motivation to combine Hasse with Chen is to combine features in the same / related field of invention of encoding / decoding with context models [Hasse Paragraphs 11 – 15] in order to improve processing speed and support parallelized architectures for video encoding / decoding [Hasse Paragraphs 12 – 15 where the Examiner observes at least KSR Rationales (D) or (F) are also applicable].
The motivation to combine Balcilar with Hasse and Chen is to combine features in the same / related field of invention of initializing / updating state transitions [Balcilar Paragraphs 2 – 6] in order to improve coding efficiency [Balcilar Paragraphs 139 and 186 – 187 where the Examiner observes at least KSR Rationales (D) or (F) are also applicable].
The motivation to combine Xiu with Balcilar, Hasse, and Chen is to combine features in the same / related field of invention of quantization techniques [Xiu Paragraph 2] in order to improve coding efficiency [Xiu Paragraphs 2 – 4 where the Examiner observes at least KSR Rationales (D) or (F) are also applicable].
This is the motivation to combine Chen, Hasse, Balcilar, and Xiu which will be used throughout the Rejection.
Regarding claim 3, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein adjusting the CDF based on whether the first scalar quantizer or the second scalar quantizer is selected comprises [See claim 1 for citations]:
identifying one or more initialization values for the CDF [Chen Paragraphs 104 – 109 and 112 – 115 (initialization parameters for the context / CDF), 119 – 121, and 129 – 137 (syntax for initialization) in combination with Hasse’s initialization techniques in at least Paragraphs 138 – 142 (including the tables where a dependent quantizer selects the initial table), 147 – 154 (other syntax elements to use to initialize the context table / CDF), 228 – 237 and 244 – 252 (other methods to initialize states variables for a context model Table included)]; and
initializing the CDF using the one or more initialization values [Chen Paragraphs 104 – 109 and 112 – 115 (initialization parameters for the context / CDF), 119 – 121, and 129 – 137 (syntax for initialization) in combination with Hasse’s initialization techniques and suggested syntax elements to initialize context models in at least Paragraphs 138 – 142 (including the tables where a dependent quantizer selects the initial table), 147 – 154 (other syntax elements to use to initialize the context table / CDF), 228 – 237 and 244 – 252 (other methods to initialize states variables for a context model Table included)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 5, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein the syntax element indicates a transform coefficient magnitude for the at least one block [Chen Paragraphs 94 – 97 (syntax elements indicating quantized transform coefficients encoded and decoded) wither further details in Balcilar Figure 8 as well as Paragraphs 128 – 136 (DQ performed on transform coefficients based on levels / quantization of the coefficients with the sign data hidden (thus rendering obvious magnitudes are processed further shown in Paragraphs 124 – 127)), 137 – 142 (mapping / signaling transform coefficient level), and 152 – 160 (Table 5 included); Xiu Figures 5 – 7 as well as Paragraphs 92 – 100 (states of DQ based on transform coefficient level generally regarded as a magnitude / absolute value to one of ordinary skill in the art as shown in the expressions in (a) and (b))].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 6, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
identifying an update rate for the CDF [Chen Paragraphs 105 – 109 (such as the “SlopeIdx” in equation 2), 113 – 114 and 119 (adaptation rate is an obvious variant of the claimed “update rate” to one of ordinary skill in the art such as in Hasse Paragraphs 136 – 141 and 178 – 185 (adaptation rate affecting the updating of the context model and the agility / speed of the update)]; and
updating the CDF in accordance with the identified update rate [Chen Paragraphs 105 – 109, 113 –119 (including equations 5 – 8 as adaptation rate is used in updating the context model is an obvious variant of the claimed “update rate” to one of ordinary skill in the art such as in Hasse Paragraphs 136 – 141 and 178 – 185 (adaptation rate affecting the updating of the context model and the agility / speed of the update)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 7, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein identifying the update rate comprises identifying a set of offsets corresponding to the update rate [Chen Paragraphs 103 – 109 (see at least the “OffsetIdx” as an obvious variant of the claimed “offset” to one of ordinary skill in the art) or alternatively in Hasse Paragraphs 142 – 154 and 161 (see the offsets including those in Table 2 regarding accessing models / updates to models)], and
wherein different sets of offsets are defined for the update rate based on whether the first scalar quantizer or the second scalar quantizer is selected [Hasse Paragraphs 142 – 154 (signaling use of DQ to affect offsets and context selection) and 161 – 180 (see the offsets including those in Table 2 regarding accessing models / updates to models where the shift0 and shift1 parameters are functions of the quantizer states) and 230 – 234; Figures 5 – 7 and 9 – 10 as well as Xiu Paragraphs 104 – 113 (need to shift / offsets for processing information based on DQ including weights with rate considerations – motivation to combine with Paragraphs 114 – 132), 114 – 120 (quantization based offsets) and 121 – 132 (various embodiments selecting the offsets and weights to use to affect changes to the model / updates to weights affecting states / updates)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 8, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein the syntax element is decoded using a multi-hypothesis arithmetic coding [Chen Paragraphs 95 – 97 (various syntax elements to encode / decode with a CDF / context table) and 112 – 120 (MHP (multi-hypothesis probability estimation) in combination with Hasse Paragraphs 95 – 98 (first and second hypotheses used rendering obvious the multiple hypotheses claimed and further tests in Paragraphs 101 – 108 and 280 – 282 (see embodiments 61 – 62 and 67 – 68))], and
wherein a respective CDF for each hypothesis of the multi-hypothesis arithmetic coding is adjusted based on whether the first scalar quantizer or the second scalar quantizer is selected [Chen Paragraphs 95 – 97 (various syntax elements to encode / decode with a CDF / context table), 112 – 120 (MHP (multi-hypothesis probability estimation – see in particular the quantization step used in Paragraph 114 combinable with Xiu Paragraphs 94 – 100 (states of dependent quantizer with hypotheses as taught in Paragraph 132))) and 130 – 136 (see syntax and initialization for the MHP depending on quantization) in combination with Hasse Paragraphs 95 – 98 (first and second hypotheses used rendering obvious the multiple hypotheses claimed and further tests in Paragraphs 101 – 111, 116, 136 – 148 (dependent quantizer as in 229 – 234 (dependent quantization affect context models) and 280 – 282 (see embodiments 61 – 62 and 67 – 68))].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 10, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
receiving video data comprising a plurality of blocks [Chen Figures 1 (subfigures included in particular reference characters 20, 100 (encoder), 400, 410, 420, 430, and 440 (plurality of blocks for the video input)) as well as Paragraphs 46 – 47 (block based video processing)];
encoding at least one block of the plurality of blocks [Chen Figure 1 (subfigures included in particular reference characters 100, 106 (entropy coder) and 114 (output of encoder)) as well as Paragraphs 47 – 51 (entropy encoding the blocks processed in the encoder)];
selecting a cumulative distribution function (CDF) for encoding a syntax element based on whether a first scalar a state of a dependent quantizer or a second scalar quantizer is selected for dependent scalar quantization of transform coefficients corresponding to the plurality of blocks [Chen Figures 1 (subfigures included) and 5 – 6 as well as Paragraphs 94 – 97 (syntax elements indicating quantized transform coefficients encoded and decoded), 103 – 109 (initializing the CDF / context model (Paragraph 104) using QP dependent parameter to initialize / adjust the context model to use – combinable with the teachings of Hasse) and 116 – 120 (signaling in a slice (or picture) header initialization information for the context table / model and if a dependent quantizer / quantization state is used); Hasse Figure 3 as well as Paragraphs 80 – 83 (arithmetic / entropy decoding based on a dependent quantization) and 133 – 140 (initialization of the context model based on the state of a dependent quantizer including Table 1) and Paragraphs 179 – 199 (adjusting / adapting the CDF / probability state of the context model); Balcilar Figure 8 as well as Paragraphs 130 – 136 (DQ performed on transform coefficients based on levels / quantization of the coefficients) and 152 – 160 (Table 5 included); Xiu Figures 5 – 7 as well as Paragraphs 94 – 100 (states of DQ based on transform coefficients)],
wherein the syntax element indicates encoding information about the at least one block [Chen Figures 1 and 2 (subfigures included and in particularly reference character 201 and 202) and 5 – 6 as well as Paragraphs 78 – 82 (decoding syntax elements), 96 (transform coefficient syntaxes), 105 – 107 (context model / probability used to decode the syntax elements), and 116 – 120 (initialization syntax – combinable with Balcilar) and 135 – 138 (signaling initialization of the context model / table to use and if the information is in a bock of CTU thus the block is decoded based on signaling syntax elements); Balcilar Figures 7 – 8 as well as Paragraphs 136 – 143 (transmitting the context model and decoding syntax elements / information from the syntax elements with the context model / probability information) 146 – 150 (enabling dependent quantizers on a picture level to modify / combine with Chen)];
adjusting the CDF using one or more values based on whether the first scalar quantizer or the second scalar quantizer is selected [Chen Figures 8 – 9 as well as Paragraphs 106 – 109 (initialization based on parameters and quantizers), 114 – 121 (weights to adapt probabilities as functions of the quantization step size and parity state) and 180 – 188 in combination with Balcilar Paragraphs 129 – 130 (scalar quantizers) and 136 – 144 (quantization states Q0 and Q1 are used to adjust the CDF / context with dependent / scalar quantizers in Paragraphs 148 – 153) or Hasse Figure 3 as well as Paragraphs 80 – 83 (arithmetic / entropy decoding based on a dependent quantization), 133 – 140 (initialization of the context model based on the state of a dependent quantizer including Table 1), and 179 – 199 (adjusting / adapting the CDF / probability state of the context model); Xiu Figure 5 – 7 as well as Paragraphs 95 – 100 (context selection and updates to contexts based on the quantization state) and 131 – 132 (updating the context / weights to combine with Chen)];
encoding the syntax element using the adjusted CDF [Chen Figure 1 (subfigures included in particular reference characters 100, 106 (entropy coder) and 114 (output of encoder)) as well as Paragraphs 47 – 51 (entropy encoding the blocks processed in the encoder including syntax elements), 96, 120, and 136 – 140 (tables included with signaling encoded syntax elements related to the processing of blocks into a bitstream for a decoder)]; and
signaling the encoded syntax element in a video bitstream [Chen Figure 1 (subfigures included in particular reference characters 100, 106 (entropy coder) and 114 (output of encoder)) as well as Paragraphs 47 – 51 (entropy encoding the blocks processed in the encoder including syntax elements), 96, 116 – 120 (initialization syntax – combinable with Balcilar), and 136 – 140 (tables included with signaling encoded syntax elements related to the processing of blocks into a bitstream for a decoder); Balcilar Figures 7 – 8 as well as Paragraphs 136 – 143 (transmitting the context model and information from the syntax elements with the context model / probability information) and 146 – 150 (enabling dependent quantizers on a picture level to modify / combine with Chen)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu and Chen Paragraphs 54, 72, and 75 – 78 render obvious encoding generating the bitstream for the decoder to process as the faithful inverse operation of the encoder thus similar motivation exists.
Regarding claim 21, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein the first scalar quantizer comprises reconstruction levels at even multiples of a quantization step size [See next limitation for citations], and the second scalar quantizer comprises reconstruction levels at odd multiples of the quantization step size [Balcilar Figures 4 – 6 as well as Paragraphs 129 – 134 (quantizer states for odd and even multiples (especially in Paragraphs 130 and 134) for Q0 and Q1 (Paragraphs 133))].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 22, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein for an inter predicted frame, the one or more initialization values for the CDF are initialized from updated CDF values of the syntax element in one or more reference frames [Chen Paragraph 113 (copied parameters for inter coded slices / frames to apply to Paragraphs 98 (inter frame prediction) with syntax elements suggested in Paragraphs 185 and 195); Balcilar Figure 9 as well as Paragraphs 163 – 166 (carrying over information from inter predicted blocks / slices / frames)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Regarding claim 23, Chen teaches updating / initialization of context tables based on dependent quantization values with syntax elements to signal such updates. Hasse teaches various features to update the context tables / models (or probabilities adaptation rates or windows / how much data to accumulate). Balcilar teaches syntax elements to use instead of those taught by Chen for dependent quantizers to update / initialize context models. Xiu teaches dependent quantizers to adjust / modify probability models with transform level / coefficient considerations and teaching when to signal by-pass modes based on the quantizer parity.
It would have been obvious to one of ordinary skill art before the effective filing date of the claimed invention to modify the teachings of Chen to include additional context model parameters and update information as taught by Hasse; and to use syntax elements and initialization / adjustment techniques as taught by Balcilar; and with Xiu’s parity considerations for signaling by-pass mode and transform coefficient levels affecting quantizer states. The combination teaches
wherein the syntax element is bypass coded or context coded based on whether the first scalar quantizer or the second scalar quantizer is selected [Hasse Paragraphs 161 – 166 and 199 (bypass bins for selection as function of DQ quantizers); Balcilar Paragraphs 84 and 142 – 147 (by-pass due to state transitions / parameters associated with DQ quantizers and the parity) and similarly Xiu Paragraphs 94 – 100 (see the ZeroPos parameter and decision based on Qstate to bypass code the syntax element as Qstate is based on Q0 and Q1)].
See claim 1 for the motivation to combine Chen, Hasse, Balcilar, and Xiu.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Coban, et al. (US PG PUB 2019/0387259 A1 referred to as “Coban” throughout) in Paragraph 90 and Figures 4 – 6 and 12 renders obvious selection of context models / CDFs and the changes / updates based on QPs / quantizers.
Reference found in updated search and consideration: Karczewicz, et al. (US PG PUB 2025/0234044 A1 referred to as “Karczewicz” throughout) teaches using dependent quantizers to code transform coefficients. Karczewicz, et al. (US PG PUB 2020/0077117 A1 referred to as “Kar” throughout) teaches in Paragraphs 140 – 150 of bypass coding considerations based on parity level states / indicators.
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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/TYLER W. SULLIVAN/Primary Examiner, Art Unit 2487
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