Dolby Laboratories Licensing Corporation

Future Wei Technologies, Inc.

Vid Scale, Inc.

Dobly Laboratories Licensing Corporation

Taoran Lu

Peng Yin

Tao Chen

Walter J Husak

Fangjun Pu

Sean Thomas McCarthy

Guan-Ming Su

Robin Atkins

Jaclyn Anne Pytlarz

Yu Huang

Dapeng Oliver Wu

Hong Heather Yu

Zheng Yuan

Yuwen He

Sean Thomas Mccarthy

Glenn N Dickins

Jun Tian

Samir N Hulyalkar

Xuejing Sun

Gopi Lakshminarayanan

Hariharan Ganapathy

Hariharan Ganapathy-Kathirvelu

Hong Heather Wu

Zhifeng Chen

Arjun Arora

An input image represented in an input domain is received from an input video signal. Forward reshaping is performed on the input image to generate a forward reshaped image represented in a reshaped image domain. Non-reshaping encoding operations are performed to encode the reshaped image into an encoded video signal. At least one of the non-reshaping encoding operations is implemented with an ML model that has been previously trained with training images in one or more training datasets in a preceding training stage. A recipient device of the encoded video signal is caused to generate a reconstructed image from the forward reshaped image.

Reshaper for learning based image/video coding

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.

Integrated image reshaping and video coding

Methods and systems for canvas size scalability across the same or different bitstream layers of a video coded bitstream are described. Offset parameters for a conformance window, a reference region of interest (ROI) in a reference layer, and a current ROI in a current layer are received. The width and height of a current ROI and a reference ROI are computed based on the offset parameters and they are used to generate a width and height scaling factor to be used by a reference picture resampling unit to generate an output picture based on the current ROI and the reference ROI.

Canvas size scalable video coding

Methods are described to communicate source color volume information in a coded bitstream using SEI messaging. Such data include at least the minimum, maximum, and average luminance values in the source data plus optional data that may include the color volume x and y chromaticity coordinates for the input color primaries (e.g., red, green, and blue) of the source data, and the color x and y chromaticity coordinates for the color primaries corresponding to the minimum, average, and maximum luminance values in the source data. Messaging data signaling an active region in each picture may also be included.

Source color volume information messaging

Methods and systems for frame rate scalability are described. Support is provided for input and output video sequences with variable frame rate and variable shutter angle across scenes, or for input video sequences with fixed input frame rate and input shutter angle, but allowing a decoder to generate a video output at a different output frame rate and shutter angle than the corresponding input values. Techniques allowing a decoder to decode more computationally-efficiently a specific backward compatible target frame rate and shutter angle among those allowed are also presented.

Frame-rate scalable video coding

Given a sequence of images in a first codeword representation, methods, processes, and systems are presented for image reshaping using rate distortion optimization, wherein reshaping allows the images to be coded in a second codeword representation which allows more efficient compression than using the first codeword representation. Syntax methods for signaling reshaping parameters are also presented.

Image reshaping in video coding using rate distortion optimization

A quantization parameter signalling mechanism for both SDR and HDR content in video coding is described using two approaches. The first approach is to send the user-defined Qptable directly in high level syntax. This leads to more flexible and efficient QP control for future codec development and video content coding. The second approach is to signal luma and chroma QPs independently. This approach eliminates the need for Qptables and removes the dependency of chroma quantization parameter on luma QP.

Quantization parameter signaling

In a method to improve the coding efficiency of high-dynamic range (HDR) images, a decoder parses sequence processing set (SPS) data from an input coded bitstream to detect that an HDR extension syntax structure is present in the parsed SPS data. It extracts from the HDR extension syntax structure post-processing information that includes one or more of a color space enabled flag, a color enhancement enabled flag, an adaptive reshaping enabled flag, a dynamic range conversion flag, a color correction enabled flag, or an SDR viewable flag. It decodes the input bitstream to generate a preliminary output decoded signal, and generates a second output signal based on the preliminary output signal and the post-processing information.

Signal reshaping and coding for HDR and wide color gamut signals

In a method to improve backwards compatibility when decoding high-dynamic range images coded in a wide color gamut (WCG) space which may not be compatible with legacy color spaces, hue and/or saturation values of images in an image database are computed for both a legacy color space (say, YCbCr-gamma) and a preferred WCG color space (say, IPT-PQ). Based on a cost function, a reshaped color space is computed so that the distance between the hue values in the legacy color space and rotated hue values in the preferred color space is minimized. HDR images are coded in the reshaped color space. Legacy devices can still decode standard dynamic range images assuming they are coded in the legacy color space, while updated devices can use color reshaping information to decode HDR images in the preferred color space at full dynamic range.

Signal reshaping for high dynamic range signals

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Taoran Lu