In-loop Filtering Virtual Boundary Signaling
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Solution Overview
Problem
High-resolution, high-quality image/video data requires efficient compression technologies to reduce transmission and storage costs, especially with the increasing demand for immersive media like VR and AR, where existing image/video coding methods are inefficient in signaling and filtering across virtual boundaries.
Innovation Solution
The implementation of a method and apparatus for image/video coding that applies efficient filtering techniques, including 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 these boundaries, optimizing hardware resource usage and filtering performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If in-loop filtering is performed across virtual boundaries to improve visual quality, then subjective/objective visual quality is improved, but hardware resource consumption increases
Solution Approach 1:
The patent applies different filtering strategies to different regions: virtual boundaries are identified and classified into types (e.g., slice boundaries, tile boundaries), and filtering is selectively applied or disabled based on boundary type and local image characteristics. This local differentiation improves visual quality at boundaries without uniformly increasing hardware resource consumption across the entire image.
Solution Approach 2:
The patent segments the image into regions separated by virtual boundaries (slices, tiles, CTU boundaries) and applies filtering selectively to each segment. By dividing the processing into boundary-specific and non-boundary-specific operations, the system can optimize hardware resource usage by disabling filtering in regions where it provides minimal benefit while maintaining it where needed for quality.
2Manufacturing precision
If traditional signaling methods are used for in-loop filtering parameters, then filtering can be applied, but signaling efficiency is low
Solution Approach 1:
The patent performs preliminary classification of virtual boundaries and pre-determines filtering parameters based on boundary type and local image characteristics before actual filtering execution. This preliminary action allows the system to signal only essential filtering parameters rather than complete filtering configurations, improving signaling efficiency while maintaining filtering performance.
Solution Approach 2:
The patent changes filtering parameters (such as filter strength, filter type, or enable/disable flags) based on the type of virtual boundary and local image characteristics. By dynamically adjusting parameters rather than using fixed signaling, the system achieves better filtering performance with more efficient signaling, as only relevant parameter changes need to be transmitted.
Data Source
AI summary
According to embodiments of the present document, information for performing in-loop filtering by crossing virtual boundaries can be efficiently signaled. In one embodiment, the value of a virtual boundary-related flag signaled through a picture header can be determined on the basis of the value of a virtual boundary-related flag signaled through an SPS.