Image Coding Device Virtual Boundary Loop Filtering Control
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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, and storage due to the high amount of information required, and existing loop filtering methods are inefficient in signaling information effectively.
Innovation Solution
The implementation of a method and apparatus for image/video coding that includes efficient filtering techniques like deblocking, sample adaptive offset (SAO), and adaptive loop filtering (ALF) based on virtual boundaries, with a sequence parameter set (SPS) flag indicating whether in-loop filtering is performed across virtual boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional loop filtering methods are used for high-resolution image/video compression, then compression is achieved, but transmission and storage costs increase due to high bit requirements
Solution Approach 1:
The image/video is divided into multiple tiles, and loop filtering is selectively applied based on tile boundaries and virtual boundaries. This segmentation allows the system to apply filtering only where necessary, reducing overall bit requirements while maintaining compression efficiency for high-resolution content.
Solution Approach 2:
Different filtering strategies are applied to different regions: strong filtering at actual boundaries (slice, tile, CTU boundaries) and selective filtering at virtual boundaries. This local quality approach ensures high visual quality where needed while reducing bit consumption in regions where filtering is less critical.
2Manufacturing precision
If in-loop filtering is performed across all boundaries including virtual boundaries, then visual quality improves, but hardware resources increase
Solution Approach 1:
The filtering behavior is made dynamic through the virtual boundaries enabled flag, which allows the system to adaptively enable or disable filtering across virtual boundaries based on content characteristics and resource availability. This dynamic approach maintains high visual quality when needed while conserving hardware resources when virtual boundary filtering is not beneficial.
Solution Approach 2:
The system changes the filtering parameter (enabled/disabled state) based on the virtual boundaries enabled flag in the SPS. This parameter change allows flexible control over hardware resource usage while maintaining the capability to achieve high visual quality when the flag is set appropriately.
3Ease of operation
If existing signaling methods are used for loop filtering control, then filtering is applied, but information signaling efficiency is insufficient
Solution Approach 1:
The virtual boundaries enabled flag is set in advance in the SPS (Sequence Parameter Set), allowing the decoder to pre-configure filtering behavior before processing actual image data. This preliminary signaling improves efficiency by avoiding the need for frequent in-band signaling decisions during decoding.
Solution Approach 2:
The virtual boundaries enabled flag serves multiple functions: it controls filtering across virtual boundaries, implicitly defines tile boundaries, and provides a unified control mechanism for various filtering operations. This multi-functionality reduces the overall signaling overhead compared to separate control mechanisms.
Data Source
AI summary
In a decoding method performed by a decoding apparatus according to embodiments of the present document, whether signaling of information related to virtual boundaries is present in a sequence parameter set (SPS) or picture header information may be determined based on a virtual boundaries enabled flag.