# US 12,015,786 B2 · Integrated image reshaping and video coding

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- Number: US 12,015,786 B2
- Document ID: US12015786B2
- Status: Granted
- Kind: B2
- Application number: 17/940,819
- Filed: 2022-09-08
- Published: 2023-01-26
- Granted: 2024-06-18
- Earliest claimed: 2017-06-29
- Assignees: Dolby Laboratories Licensing Corporation
- Applicants: Dolby Laboratories Licensing Corporation
- Inventors: Taoran Lu; Fangjun Pu; Peng Yin; Tao Chen; Walter J. Husak
- Web page: https://patentgrep.com/patent/US12015786B2

## CPC

- H04N 19/107: between spatial and temporal predictive coding, e.g. picture refresh
- H04N 19/159: Prediction type, e.g. intra-frame, inter-frame or bidirectional frame prediction
- H04N 19/117: Filters, e.g. for pre-processing or post-processing (sub-band filter banks H04N19/635)
- H04N 19/124: Quantisation
- H04N 19/136: Incoming video signal characteristics or properties
- H04N 19/174: the region being a slice, e.g. a line of blocks or a group of blocks
- H04N 19/176: the region being a block, e.g. a macroblock
- H04N 19/182: the unit being a pixel
- H04N 19/45: {performing compensation of the inverse transform mismatch, e.g. Inverse Discrete Cosine Transform [IDCT] mismatch}
- H04N 19/463: by compressing encoding parameters before transmission
- H04N 19/503: involving temporal prediction (adaptive coding with adaptive selection between spatial and temporal predictive coding H04N19/107; adaptive coding with adaptive selection among a plurality of temporal predictive coding modes H04N19/109)
- H04N 19/82: involving filtering within a prediction loop
- H04N 19/98: Adaptive-dynamic-range coding [ADRC]
- H04N 19/34: Scalability techniques involving progressive bit-plane based encoding of the enhancement layer, e.g. fine granular scalability [FGS]
- H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION

## Abstract

Given a sequence of images in a first codeword representation, methods, processes, and systems are presented for integrating reshaping into a next generation video codec for encoding and decoding the images, wherein reshaping allows part of the images to be coded in a second codeword representation which allows more efficient compression than using the first codeword representation. A variety of architectures are discussed, including: an out-of-loop reshaping architecture, an in-loop-for intra pictures only reshaping architecture, an in-loop architecture for prediction residuals, and a hybrid in-loop reshaping architecture. Syntax methods for signaling reshaping parameters, and image-encoding methods optimized with respect to reshaping are also presented.

## Claims

### Claim 1

An apparatus for encoding images, the apparatus comprising:
an input for accessing an input image in a first codeword representation; and a processor, wherein the processor:
generates a forward reshaping function mapping pixels of the input image to a second codeword representation;
generates an inverse reshaping function based on the forward reshaping function, wherein the inverse reshaping function maps pixels from the second coding representation to the first coding representation;
generates coded pixel regions of the input image based on input pixel regions in the input image, the forward reshaping function and the inverse reshaping function;
generates reshaping metadata which characterize the forward reshaping function based on a piecewise-linear representation; and
generates an output bitstream based on the coded pixel regions of the input image and the reshaping metadata.

### Claim 2 (depends on 1)

The apparatus of claim 1, wherein to generate the coded pixel regions of the input image the processor applies in-loop reshaping.

### Claim 3 (depends on 1)

The apparatus of claim 1, wherein for an input pixel region in the input image, to generate a coded pixel region, the processor:
computes a predicted region based on pixel data in a reference frame buffer or previously coded spatial neighbors;
generates a reshaped residual region based on the input pixel region, the predicted region, and the forward reshaping function, wherein a reshaped residual sample in the reshaped residual region is derived at least in part from forward reshaping a respective predicted sample in the predicted region;
generates a quantized residual region based on the reshaped residual region;
generates a dequantized residual region based on the quantized residual region;
generates a reconstructed pixel region based on the dequantized residual region, the predicted region, the forward reshaping function, and the inverse reshaping function; and
generates a reference pixel region to be stored on the reference frame buffer based on the reconstructed pixel region.

### Claim 4 (depends on 3)

The apparatus of claim 3, wherein generating the quantized residual region comprises:
applying a forward coding transform to the reshaped residual region to generate transformed data; and
applying a forward coding quantizer to the transformed data to generate quantized data.

### Claim 5 (depends on 4)

The apparatus of claim 4, wherein generating the dequantized residual region comprises:
applying an inverse coding quantizer to the quantized data to generate inverse-quantized data; and
applying an inverse coding transform to the inverse-quantized data to generate the dequantized residual region.

### Claim 6 (depends on 3)

The apparatus of claim 3, wherein generating the reference pixel region to be stored on the reference frame buffer comprises applying a loop filter to the reconstructed pixel region.

### Claim 7 (depends on 3)

The apparatus of claim 3, wherein generating the reshaped residual region comprises computing:
Res_r(i)=Fwd(Orig_sample(i))−Fwd(Pred_sample(i)),
where Fwd( ) denotes the forward reshaping function, Res_r(i) denotes a pixel of the reshaped residual region, Orig_sample(i) denotes a pixel of the input image region, and Pred_sample(i) denotes a pixel of the predicted region.

### Claim 8 (depends on 7)

The apparatus of claim 7, wherein generating the reconstructed pixel region comprises computing:
Recon_sample(i)=Inv(Res_d(i)+Fwd(Pred_sample(i))),
where Inv( ) denotes the inverse reshaping function, Recon_sample (i) denotes a pixel of the reconstructed pixel region and Res_d(i) denotes a pixel of the dequantized residual region representing a close approximation of the Res_r(i) pixel.

### Claim 9 (depends on 1)

The apparatus of claim 1, wherein for each segment of a piecewise linear representation of the forward reshaping function, the reshaping metadata comprise a delta absolute value and a sign of the delta absolute value.

### Claim 10 (depends on 9)

The apparatus of claim 9, wherein for bin_ce_delta_abs[i] denoting the delta absolute value for segment i, its value represents the difference of codewords allocated in segment i compared to the codewords allocated in segment i−1 (bin_ce_delta_abs[i−1]).

### Claim 11

An apparatus for decoding a coded bitstream to generate an output image in a first codeword representation, the apparatus comprising:
an input to receive a coded image partially coded in a second codeword representation; and a processor, wherein the processor:
receives reshaping metadata for the coded image;
generates based on the reshaping metadata the forward reshaping function mapping pixels from the first codeword representation to the second codeword representation;
generates based on the reshaping metadata an inverse reshaping function, wherein the inverse reshaping function maps pixels from the second codeword representation to the first codeword representation; and
decodes coded regions of the coded image based on the forward reshaping function and the inverse reshaping function to generate output pixel regions.

### Claim 12 (depends on 11)

The apparatus of claim 11, wherein the processor decodes the coded regions of the coded image based on in-loop reshaping.

### Claim 13 (depends on 11)

The apparatus of claim 11, wherein to decode a coded region, the processor:
generates a decoded reshaped residual region;
generates a predicted region based on pixels in a reference pixel buffer or previously decoded spatial neighbors;
generates a reconstructed pixel region based on the decoded reshaped residual region, the predicted region, the forward reshaping function, and the inverse reshaping function, wherein a reconstructed sample in the reconstructed pixel region is derived at least in part from forward reshaping a respective predicted sample in the predicted region;
generates an output pixel region for the output image based on the reconstructed pixel region; and
stores the output pixel region in the reference pixel buffer.

### Claim 14 (depends on 12)

The apparatus of claim 12, wherein generating the reconstructed pixel region comprises computing:
Reco_sample(i)=Inv(Res_d(i)+Fwd(Pred_sample(i))),
where Reco_sample (i) denotes a pixel of the reconstructed pixel region, Res_d(i) denotes a pixel of the decoded reshaped residual region, Inv( ) denotes the inverse reshaping function, Fwd( ) denotes the forward reshaping function, and Pred_sample(i) denotes a pixel of the predicted region.

### Claim 15 (depends on 11)

The apparatus of claim 11, wherein the metadata characterize the forward reshaping function based on a piecewise linear representation, and for each segment of the piecewise linear representation of the forward reshaping function, the reshaping metadata comprise a delta absolute value and a sign of the delta absolute value.

### Claim 16 (depends on 15)

The apparatus of claim 15, wherein for bin_ce_delta_abs[i] denoting the delta absolute value for segment i, its value represents the difference of codewords allocated in segment i compared to the codewords allocated in segment i−1 (bin_ce_delta_abs[i−1]).