Description
Book Synopsis.- Chapter 1 Introduction to Image and Video Coding
.- 1.1 Basic Concept of Image and Video Data
.- 1.2 Representative Image and Video Datasets
.- 1.3 AI-based Compression Requirement for Image and Video
.- 1.4 Image and Video Coding Performance Evaluation
.- 1.5 Organization of This Book
.- 1.6 Summary
.- Chapter 2 Fundamentals for Deep Learning-based Image and Video Coding
.- 2.1 Introduction
.- 2.2 Fundamental Knowledge of Deep Learning
.- 2.3 Autoencoder and Variational Autoencoder
.- 2.4 Principles and Framework of Deep Learning-based Image and Video Coding
.- 2.5 Summary
.- Chapter 3 Image and Video Quality Assessment and Perception Models
.- 3.1 Introduction
.- 3.2 Quality Assessment of Image and Video
.- 3.3 Just Noticeable Distortion of Image and Video
.- 3.4 Visual Attention Modeling of Image and Video
.- 3.5 Comparative Analysis
.- 3.6 Summary
.- Chapter 4 Deep Learning-based Image Coding
.- 4.1 Introduction
.- 4.2 Representative Methods of Lossless Image Coding
.- 4.3 Representative Methods of Lossy Image Coding
.- 4.4 Comparative Analysis
.- 4.5 Summary
.- Chapter 5 Deep Learning-based Video Coding
.- 5.1 Introduction
.- 5.2 Framework and Key Components
.- 5.3 Representative Methods of Video Coding
.- 5.4 Comparative Analysis
.- 5.5 Summary
.- Chapter 6 Deep Learning-based 3D and Multimodal Coding
.- 6.1 Introduction
.- 6.2 Overall Framework and Datasets
.- 6.3 Representative Methods of 3D and Multimodal Coding
.- 6.4 Comparative Analysis
.- 6.5 Summary
.- Chapter 7 Human and Machine Vision-Oriented Image and Video Coding
.- 7.1 Introduction
.- 7.2 Representative Methods of Human Perception-based Coding
.- 7.3 Representative Methods of Machine Perception-based Coding
.- 7.4 Comparative Analysis
.- 7.5 Summary
.- Chapter 8 Compression Artifacts Removal for Image and Video Coding
.- 8.1 Introduction
.- 8.2 Representative Methods of Compressed Image Artifacts Reduction
.- 8.3 Representative Methods of Compressed Video Artifacts Reduction
.- 8.4 Comparative Analysis
.- 8.5 Summary
.- Chapter 9 Deep Learning-based Image and Video Coding Standards
.- 9.1 Introduction
.- 9.2 Overview of International Standards
.- 9.3 IEEE AI-based Image and Video Coding Standard
.- 9.4 JPEG AI-based Image and Video Coding Standard
.- 9.5 MPEG Video Coding for Machines Standard
.- 9.6 MPAI End-to-End Video Coding Standard
.- 9.7 Comparative Analysis
.- 9.8 Summary
.- Chapter 10 Implementations for Deep Learning-based Image and Video Coding
.- 10.1 Introduction
.- 10.2 Basics of Neural Network Compression
.- 10.3 Software and Hardware Platforms for Acceleration
.- 10.4 Lightweight Methods for Deep Compression Network
.- 10.5 Comparative Analysis
.- 10.6 Summary
.- Chapter 11 Open Source Projects for Deep Learning-based Image and Video Coding
.- 11.1 Introduction
.- 11.2 Representative Open Source Projects for Image Coding
.- 11.3 Representative Open Source Projects for Video Coding
.- 11.4 Comparative Analysis
.- 11.5 Summary
.- Chapter 12 Future Works for AI-based Image and Video Coding
.- 12.1 Future Work on Quality Assessment and Perception Models for Image and Video
.- 12.2 Future Work on Deep Learning-based for Image Coding
.- 12.3 Future Work on Deep Learning-based for Video Coding
.- 12.4 Future Work on Deep Learning-based for 3D and Multimodal Coding
.- 12.5 Future Work on Human and Machine Vision Oriented Image and Video Coding
.- 12.6 Future Work on Compression Artifacts Removal for Image and Video Coding
.- 12.7 Future Work on Deep Learning-based Image and Video Coding Standards
.- 12.8 Future Work on Implementations for Deep Learning-based Image and Video Coding
.- 12.9 Future Work on Open Source Projects for Deep Learning-based Image and Video Coding.
