Versatile Video Coding (VVC) : Machine Learning and Heuristics / by Mário Saldanha, Gustavo Sanchez, César Marcon, Luciano Agostini.

Format:

Book

Author/Creator:

Saldanha, Mário, author.

Series:

Synthesis Lectures on Engineering, Science, and Technology, 2690-0327

Language:

English

Subjects (All):

Electronic circuits.

Signal processing.

Embedded computer systems.

Electronic Circuits and Systems.

Signal, Speech and Image Processing.

Embedded Systems.

Local Subjects:

Electronic Circuits and Systems.

Signal, Speech and Image Processing.

Embedded Systems.

Physical Description:

1 online resource (128 pages)

Edition:

1st ed. 2022.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2022.

Summary:

This book discusses the Versatile Video Coding (VVC), the ISO and ITU state-of-the-art video coding standard. VVC reaches a compression efficiency significantly higher than its predecessor standard (HEVC) and it has a high versatility for efficient use in a broad range of applications and different types of video content, including Ultra-High Definition (UHD), High-Dynamic Range (HDR), screen content, 360º videos, and resolution adaptivity. The authors introduce the novel VVC tools for block partitioning, intra-frame and inter-frames predictions, transforms, quantization, entropy coding, and in-loop filtering. The authors also present some solutions exploring VVC encoding behavior at different levels to accelerate the intra-frame prediction, applying statistical-based heuristics and machine learning (ML) techniques. This book includes: A high-level description of the VVC novel encoding tools; A detailed description ofthe VVC intra-frame prediction; A deep statistical assessment of the VVC intra-frame prediction behavior; Five algorithms to reduce the VVC intra-frame prediction encoding effort.

Contents:

Introduction

Versatile Video Coding

VVC Intra-Frame Prediction

State-of-the-Art Overview

Performance Analysis of VVC Intra-Frame Prediction

Heuristic Based Fast Multi-Type Tree Decision Scheme for Luminance

Light Gradient Boosting Machine Configurable Fast Block Partitioning for Luminance

Learning-Based Fast Decision for Intra-Frame Prediction Mode Selection for Luminance

Fast Intra-Frame Prediction Transform for Luminance Using Decision Trees

Heuristic Based Fast Block Partitioning Scheme for Chrominance

Conclusions.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Saldanha, Mário Versatile Video Coding (VVC)

ISBN:

3-031-11640-2