Prosecution Insights
Last updated: April 19, 2026
Application No. 19/058,931

TECHNIQUES FOR SCALING A RATE-DISTORTION MULTIPLIER WHEN PERFORMING TRELLIS CODED QUANTIZATION

Non-Final OA §103
Filed
Feb 20, 2025
Examiner
FEREJA, SAMUEL D
Art Unit
2487
Tech Center
2400 — Computer Networks
Assignee
Netflix Inc.
OA Round
1 (Non-Final)
75%
Grant Probability
Favorable
1-2
OA Rounds
2y 8m
To Grant
86%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allow Rate
458 granted / 614 resolved
+16.6% vs TC avg
Moderate +12% lift
Without
With
+11.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
66 currently pending
Career history
680
Total Applications
across all art units

Statute-Specific Performance

§101
3.6%
-36.4% vs TC avg
§103
64.1%
+24.1% vs TC avg
§102
13.8%
-26.2% vs TC avg
§112
7.9%
-32.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 614 resolved cases

Office Action

§103
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 . Information Disclosure Statement The information disclosure statements (IDS) were submitted on 11/18/2025. The submission 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 § 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 of this title, 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 1-3, 5, 8-15 & 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Karczewicz et al. (US 20240414339, hereinafter Karczewicz) in view of Coban et al. (US 20190387259, hereinafter Coban). Regarding Claim 1, Karczewicz discloses a computer-implemented method for encoding video data, the method comprising: generating a vector of transform coefficients of prediction residues that are associated with a block of source video data ([0022], a video encoder performs a transform (e.g., discrete cosine transform (DCT)) on the residual values to generate coefficient values); computing a block multiplier scaling value ([0076], FIG. 7, Coefficients in states 0 and 1 use the Q0 (even integer multiples of step size) quantizer. Coefficients in states 2 and 3 use Q1 (odd integer multiples of step size) quantizer. That is, video encoder 200 and video decoder 300 may quantize or inverse-quantize, as appliable, coefficients using quantizer Q0 (e.g., even integer multiples of step size Δ) if the state of state machine 700 is 0 or 1. Video encoder 200 and video decoder 300 may quantize or inverse-quantize, as appliable, coefficients using quantizer Q1 (e.g., odd integer multiples of step size Δ) if the state of state machine 700 is 2 or 3); computing a first multiplier based on the block multiplier scaling value ([0074] FIG. 6, using two scalar quantizers in quantization level mapping 600: first quantizer Q0 maps the transform coefficient levels, also called quantization levels, to even integer multiples of the quantization step size Δ. The second quantizer Q1 maps the transform coefficient levels to odd integer multiples of quantization step size Δ or to zero; [0076], FIG. 7, Coefficients in states 0 and 1 use the Q0 (even integer multiples of step size) quantizer. Coefficients in states 2 and 3 use Q1 (odd integer multiples of step size) quantizer; [0088] FIG. 8, two scalar quantizers the first quantizer Q0′ and the second quantizer Q1′); PNG media_image1.png 388 428 media_image1.png Greyscale performing one or more trellis coded quantization operations on the vector of transform coefficients using the first multiplier to generate a vector of quantization indices ([0072] using quantization offset scheme for dependent quantization, such as Trellis Coded Quantization (TCQ) to determine quantization offsets; [0089] use separate quantization offsets or inverse-quantization offsets (e.g., offset values) for state driven two quantizers used in TCQ instead of using one common one for both quantizers. Additionally, in some examples, luma and chroma components may use separate offsets for respective quantization); and performing one or more entropy coding operations on the vector of quantization indices to generate an encoded version of the block of source video data ([0065], video encoder scans the transform coefficients, producing a one-dimensional vector from the two-dimensional matrix including the quantized transform coefficients and encodes the one-dimensional vector, e.g., according to context-adaptive binary arithmetic coding (CABAC)). Karczewicz does not explicitly disclose computing the block multiplier scaling value based on contextual metadata. Coban teaches computing the block multiplier scaling value based on contextual metadata ([0115] Trellis Coded Quantization (TCQ) using a significance map (or greater than 1 or 2 flags) using a parity of a partial set of syntax elements, deriving the state machine based on a parity of the number of nonzero coefficients in a neighborhood of coefficient that is being coded; [0120] TCQ using a significance map to determine contexts for context encoding values of syntax elements, such as significant coefficient flags, greater than 1 flags, greater than 2 flags, or the like). Therefore, it would have been obvious to one ordinary skill in the art before the effective filing date of the claimed invention to modify the teachings of step size scaling value based on contextual metadata as taught by Coban ([0120]) into the encoding & decoding system of Karczewicz in order to enable achieving switching between context sets by changing the parity of the level of the previous coefficients so as to minimize residual differential (RD) cost and improve a computation efficiency of a video encoder and/or a video decoder (Coban, [0173]). Regarding Claim 2, Karczewicz in view of Coban discloses the computer-implemented method of claim 1, Karczewicz discloses further comprising receiving a plurality of transform coefficients from a prediction engine included in an encoder, wherein the plurality of transform coefficients is used to generate the vector of transform coefficients ([0074] FIG. 6, using two scalar quantizers in quantization level mapping 600: first quantizer Q0 maps the transform coefficient levels, also called quantization levels, to even integer multiples of the quantization step size Δ. The second quantizer Q1 maps the transform coefficient levels to odd integer multiples of quantization step size Δ or to zero; [0088] FIG. 8, two scalar quantizers used: the first quantizer Q0′ and the second quantizer Q1′). Regarding Claim 3, Karczewicz in view of Coban discloses the computer-implemented method of claim 1, Coban discloses wherein the contextual metadata includes at least one of a coding plane type, a frame type, a position within a prediction structure, a block type, a block size, or transform coefficient energy levels ([0115] Trellis Coded Quantization (TCQ) using a significance map (or greater than 1 or 2 flags) using a parity of a partial set of syntax elements, deriving the state machine based on a parity of the number of nonzero coefficients in a neighborhood of coefficient that is being coded; [0120] TCQ using a significance map to determine contexts for context encoding values of syntax elements, such as significant coefficient flags, greater than 1 flags, greater than 2 flags, or the like). The same reason or rational of obviousness motivation applied as used above in claim 1. Regarding Claim 4, Karczewicz in view of Coban discloses the computer-implemented method of claim 3, Coban discloses wherein at least a portion of the contextual metadata associated with the transform coefficients is acquired from a prediction engine included in an encoder ([0115] Trellis Coded Quantization (TCQ) using a significance map (or greater than 1 or 2 flags) using a parity of a partial set of syntax elements, deriving the state machine based on a parity of the number of nonzero coefficients in a neighborhood of coefficient that is being coded; [0120] TCQ using a significance map to determine contexts for context encoding values of syntax elements, such as significant coefficient flags, greater than 1 flags, greater than 2 flags, or the like). The same reason or rational of obviousness motivation applied as used above in claim 1. Regarding Claim 5, Karczewicz in view of Coban discloses the computer-implemented method of claim 1, Karczewicz discloses further comprising transmitting the vector of quantization indices to an entropy coding engine that performs the one or more entropy coding operations ([0074] FIG. 6, using two scalar quantizers in quantization level mapping 600: first quantizer Q0 maps the transform coefficient levels, also called quantization levels, to even integer multiples of the quantization step size Δ. The second quantizer Q1 maps the transform coefficient levels to odd integer multiples of quantization step size Δ or to zero; [0088] FIG. 8, two scalar quantizers used: the first quantizer Q0′ and the second quantizer Q1′). Regarding Claim 6, Karczewicz in view of Coban discloses the computer-implemented method of claim 1, Karczewicz discloses wherein the first multiplier comprises a rate-distortion multiplier for trellis coded quantization ([0195], FIGS. 6 and 8, a quantization level may also control which offset value is selected. For instance, the processing circuitry of video encoder 200 or video decoder 300 may determine a quantization level for the coefficient of a current block The quantization level may be represented as yi. Video encoder 200 may determine yi based on a rate-distortion calculation, and may signal information that video decoder 300 uses to determine yi ). Regarding Claim 7, Karczewicz in view of Coban discloses the computer-implemented method of claim 6, Karczewicz discloses wherein the one or more trellis coded quantization operations are performed in accordance with a second cost function that includes a rate term and a distortion term ([0195], FIGS. 6 and 8, a quantization level may also control which offset value is selected. For instance, the processing circuitry of video encoder 200 or video decoder 300 may determine a quantization level for the coefficient of a current block The quantization level may be represented as yi. Video encoder 200 may determine yi based on a rate-distortion calculation, and may signal information that video decoder 300 uses to determine yi ). Regarding Claim 8, Karczewicz in view of Coban discloses the computer-implemented method of claim 7, Karczewicz discloses wherein either the rate term or the distortion term included in the second cost function is weighted using the first multiplier ([0195], FIGS. 6 and 8, a quantization level may also control which offset value is selected. For instance, the processing circuitry of video encoder 200 or video decoder 300 may determine a quantization level for the coefficient of a current block The quantization level may be represented as yi. Video encoder 200 may determine yi based on a rate-distortion calculation, and may signal information that video decoder 300 uses to determine yi ). Regarding Claim 9, Karczewicz in view of Coban discloses the computer-implemented method of claim 7, Karczewicz discloses wherein the second cost function incorporates a tradeoff between an estimated number of bits needed by an entropy encoder to encode a sequence of transform coefficients and a distortion corresponding to the sequence of transform coefficients([0195], FIGS. 6 and 8, a quantization level may also control which offset value is selected. For instance, the processing circuitry of video encoder 200 or video decoder 300 may determine a quantization level for the coefficient of a current block The quantization level may be represented as yi. Video encoder 200 may determine yi based on a rate-distortion calculation, and may signal information that video decoder 300 uses to determine yi ). Regarding Claim 10, Karczewicz in view of Coban discloses the computer-implemented method of claim 1, Coban discloses wherein the first multiplier is not transmitted to a decoder in order to decode the encoded version of the block of source video data (([0115] Trellis Coded Quantization (TCQ) using a significance map (or greater than 1 or 2 flags) using a parity of a partial set of syntax elements, deriving the state machine based on a parity of the number of nonzero coefficients in a neighborhood of coefficient that is being coded). The same reason or rational of obviousness motivation applied as used above in claim 1. Regarding Claims 11-19, computer-readable media claims 11-19 of using the corresponding method claimed in claims 1-9, and the rejections of which are incorporated herein for the same reasons as used above. Regarding Claim 20, computer system claim 20 of using the corresponding method claimed in claim 1, and the rejections of which are incorporated herein for the same reasons as used above. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Samuel D Fereja whose telephone number is (469)295-9243. The examiner can normally be reached 8AM-5PM. 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, DAVID CZEKAJ can be reached at (571) 272-7327. 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. /SAMUEL D FEREJA/Primary Examiner, Art Unit 2487
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Prosecution Timeline

Feb 20, 2025
Application Filed
Jan 18, 2026
Non-Final Rejection — §103 (current)

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

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Prosecution Projections

1-2
Expected OA Rounds
75%
Grant Probability
86%
With Interview (+11.8%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 614 resolved cases by this examiner. Grant probability derived from career allow rate.

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