Saldanha, Mário.
Versatile Video Coding (VVC) Machine Learning and Heuristics / [electronic resource] : by Mário Saldanha, Gustavo Sanchez, César Marcon, Luciano Agostini. - 1st ed. 2022. - XI, 123 p. 50 illus., 45 illus. in color. online resource. - Synthesis Lectures on Engineering, Science, and Technology, 2690-0327 . - Synthesis Lectures on Engineering, Science, and Technology, .
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.
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.
9783031116407
10.1007/978-3-031-11640-7 doi
Electronic circuits.
Signal processing.
Embedded computer systems.
Electronic Circuits and Systems.
Signal, Speech and Image Processing.
Embedded Systems.
TK7867-7867.5
621.3815
Versatile Video Coding (VVC) Machine Learning and Heuristics / [electronic resource] : by Mário Saldanha, Gustavo Sanchez, César Marcon, Luciano Agostini. - 1st ed. 2022. - XI, 123 p. 50 illus., 45 illus. in color. online resource. - Synthesis Lectures on Engineering, Science, and Technology, 2690-0327 . - Synthesis Lectures on Engineering, Science, and Technology, .
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.
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.
9783031116407
10.1007/978-3-031-11640-7 doi
Electronic circuits.
Signal processing.
Embedded computer systems.
Electronic Circuits and Systems.
Signal, Speech and Image Processing.
Embedded Systems.
TK7867-7867.5
621.3815