In-Loop Filtering for Image Coding Subpictures
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Solution Overview
Problem
The increasing demand for high-resolution, high-quality images and videos, such as 4K or 8K, poses challenges in efficient compression, transmission, storage, and reproduction due to the high amount of information required, which leads to increased costs and resource consumption.
Innovation Solution
The proposed solution involves a method and apparatus for improving image coding efficiency by efficiently applying deblocking, sample adaptive offset (SAO), and adaptive loop filtering (ALF) techniques, while also performing in-loop filtering based on virtual boundaries and independently coding subpictures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If high-resolution, high-quality image/video compression is applied, then transmission and storage costs are reduced, but compression efficiency and visual quality are difficult to maintain simultaneously
Solution Approach 1:
The picture is divided into multiple subpictures that can be independently coded and filtered. This segmentation allows different filtering strategies to be applied to different regions, optimizing both compression efficiency and visual quality for each subpicture while reducing overall computational complexity
Solution Approach 2:
Different loop filtering modes are applied to different regions within subpictures based on local characteristics. The filtering strength and type are adapted locally rather than uniformly applied, preserving important visual details in critical regions while applying stronger compression in less important areas
2Manufacturing precision
If in-loop filtering is applied across the entire picture, then visual quality is improved, but hardware resource consumption increases
Solution Approach 1:
The filtering operation is segmented to be applied only within subpicture boundaries rather than across the entire picture. This reduces the number of filtering operations required, decreasing hardware resource consumption while maintaining visual quality within each subpicture region
Solution Approach 2:
Loop filtering is applied partially - only within subpicture regions where it provides benefit, rather than excessively applying it across all picture boundaries including inter-subpicture boundaries where it would increase complexity without proportional quality improvement
3Productivity
If subpictures are independently coded, then coding efficiency is improved, but signaling overhead increases
Solution Approach 1:
Full independent coding information is signaled only when necessary. The encoder uses default behaviors for subpicture filtering when conditions allow, signaling only deviations from the default, thereby reducing signaling overhead while maintaining coding efficiency benefits
Solution Approach 2:
The decoding process is designed to automatically infer subpicture boundaries and filtering parameters from the bitstream structure itself without requiring explicit signaling in all cases. The system self-services by using context information already present in the coded data to determine filtering behavior
Data Source
AI summary
According to an image coding method according to embodiments of the present document, information related to in-loop filtering may be efficiently signaled, and repetitive procedures for signaling subpicture-related information may be reduced.