Microsoft Technology Licensing, LLC

Meta Platforms, Inc.

University of California

Facebook, Inc.

Shankar Lakshmi Regunathan

Sridhar Srinivasan

Chih-Lung Lin

Chengjie Tu

Shijun Sun

Thomas W Holcomb

Pohsiang Hsu

Jie Liang

Minghui Xia

Gary Joseph Sullivan

Regis J Crinon

Kunal Mukerjee

Kazuhito Koishida

Kenneth Rose

Haixiong Wang

Minchuan Chen

Christian Liensberger

Rui Zhang

Cheng Chang

Harshavardhana Narayana Kikkeri

Venkatesh Krishnan

Ce Wang

Timothy E Onders

Ziv Kasperski

Drew Voegele

Cheryl Couris

Stéphane Nyombayire

Jason Walken Falk

Jean-Sebastien Brunner

Konstantin Zoryn

Roman Kogan

Francesco Lunetta

Shankar Gopalakrishnan

Miguel Llopis

Santosh Balasubramanian

Ming-Chieh Lee

Jae Hoon Kim

Qian Chen

Amit Puntambekar

Jordi Ribas-Corbera

Michael Hamilton Coward

Walid Ali

Yaming He

Guo-Wei Shieh

Bharath Siravara

Zhi Zhou

Sonal Gandhi

Ashish Dharmpal Aggarwal

Daniel Schonberg

Bruce Lin

Shuo-Jen Wu

Cosmin Vasile Stejerean

Pankaj Sethi

Techniques and tools for encoding enhancement layer video with quantization that varies spatially and/or between color channels are presented, along with corresponding decoding techniques and tools. For example, an encoding tool determines whether quantization varies spatially over a picture, and the tool also determines whether quantization varies between color channels in the picture. The tool signals quantization parameters for macroblocks in the picture in an encoded bit stream. In some implementations, to signal the quantization parameters, the tool predicts the quantization parameters, and the quantization parameters are signaled with reference to the predicted quantization parameters. A decoding tool receives the encoded bit stream, predicts the quantization parameters, and uses the signaled information to determine the quantization parameters for the macroblocks of the enhancement layer video. The decoding tool performs inverse quantization that can vary spatially and/or between color channels.

Determining chroma quantization parameter using index and quantization parameter of spatially neighboring unit

Predicting a quantization parameter for a current unit using quantization parameters of spatially neighboring units

Adaptive quantization for enhancement layer video coding

Described tools and techniques relate to signaling for DC coefficients at small quantization step sizes. The techniques and tools can be used in combination or independently. For example, a tool such as a video encoder or decoder processes a VLC that indicates a DC differential for a DC coefficient, a FLC that indicates a value refinement for the DC differential, and a third code that indicates the sign for the DC differential. Even with the small quantization step sizes, the tool uses a VLC table with DC differentials for DC coefficients above the small quantization step sizes. The FLCs for DC differentials have lengths that vary depending on quantization step size.

DC coefficient signaling at small quantization step sizes

Techniques and tools are described for decoding jointly coded information. For example, a decoder decodes a variable length code ['VLC'] signaled at macroblock level that jointly represents a transform type signal level, transform type, and subblock pattern. The decoder decodes one or more VLCs signaled at block level, each jointly representing a transform type and subblock pattern. The decoder may select between multiple VLC tables for the VLCs signaled macroblock level and/or block level.

Decoding jointly coded transform type and subblock pattern information

A video to be encoded to a plurality of different target encodings for bandwidth adaptive serving is received. The video is encoded into a plurality of different candidate encodings using different candidate encoding parameters. A quality metric is determined for each of the plurality of different candidate encodings. One or more different target quality metrics are selected for a first portion of the different target encodings based at least in part on one or more specified constraints for one or more target devices. One or more different target quality metrics are selected for a second portion of the different target encodings based at least in part on the determined quality metrics of the different candidate encodings. Based at least in part on the selected different target quality metrics for the first portion and the second portion, the plurality of different target encodings of the video is generated.

Constraint-modified selection of video encoding configurations

Techniques and tools for performing fading compensation in video processing applications are described. For example, during encoding, a video encoder performs fading compensation using fading parameters comprising a scaling parameter and a shifting parameter on one or more reference images. During decoding, a video decoder performs corresponding fading compensation on the one or more reference images.

Parameterization for fading compensation

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Shankar Lakshmi Regunathan