Video Coding With Virtual-Boundary CCALF Chroma Filtering
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Solution Overview
Problem
Existing video coding technologies face challenges in improving coding efficiency, enhancing image quality, and reducing circuit scale, particularly in the context of cross component adaptive loop filtering processes.
Innovation Solution
The implementation of a CCALF process that duplicates reconstructed samples across virtual boundaries, applies adaptive loop filtering to luma and chroma components, and combines these values to enhance the encoding and decoding of chroma components, while also incorporating a block splitter, intra and inter predictors, loop filters, transformers, quantizers, and entropy encoders/decoders to optimize video coding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If CCALF process is applied to improve chroma component quality, then image quality is improved, but device complexity increases
Solution Approach 1:
The patent divides the image into multiple blocks and processes each block independently through the CCALF process. This segmentation allows the complex filtering to be applied in a modular fashion, improving chroma quality while managing device complexity through systematic decomposition of the processing task.
Solution Approach 2:
The patent applies different filtering coefficients to different regions within blocks based on local characteristics. By adapting the filtering strength and parameters to local image features, the system achieves high chroma quality where needed while avoiding unnecessary processing in uniform regions, thus balancing quality improvement with complexity management.
2Manufacturing precision
If multiple filtering processes (CCALF and ALF) are applied to enhance image quality, then image quality is improved, but processing time increases
Solution Approach 1:
The patent combines CCALF and ALF processes into a unified filtering framework where both luma and chroma components are processed together. By merging these filtering operations and sharing computational resources, the system achieves enhanced image quality while reducing the total processing time compared to sequential independent filtering.
Solution Approach 2:
The patent performs preliminary filtering operations on luma components that can be reused for chroma component filtering. By preparing filter coefficients and intermediate results in advance during luma processing, the system reduces redundant computations and accelerates the overall filtering process while maintaining high image quality.
3Measurement precision
If reconstructed samples are duplicated across virtual boundaries to improve filtering accuracy, then filtering precision is improved, but memory usage increases
Solution Approach 1:
The patent creates duplicate copies of reconstructed samples at virtual boundaries to enable accurate filtering operations that cross block boundaries. These copied samples are essential for maintaining filtering continuity and accuracy, and the system manages memory usage by creating copies only where boundary crossing filtering is required.
Solution Approach 2:
The patent applies sample duplication selectively only at regions where virtual boundaries require crossing filtering, rather than duplicating all samples throughout the image. This partial application of the copying principle reduces memory overhead while maintaining filtering accuracy where it is most needed.
Data Source
AI summary
An encoder includes circuitry and memory coupled to the circuitry. The circuitry, in response to a first reconstructed image sample being located outside a virtual boundary, duplicates a reconstructed sample located inside and adjacent to the virtual boundary to generate the first reconstructed image sample. The circuitry generates a first coefficient value by applying a CCALF (cross component adaptive loop filtering) process to the first reconstructed image sample of a luma component. The circuitry generates a second coefficient value by applying an ALF (adaptive loop filtering) process to a second reconstructed image sample of a chroma component. The circuitry generates a third coefficient value by adding the first coefficient value to the second coefficient value, and encodes a third reconstructed image sample of the chroma component using the third coefficient value.