Cross-Component Adaptive Loop Filtering for Chroma Quality

The patent extracts and processes only the essential visual information through selective filtering operations. The ALF and CCALF processes selectively modify chroma and luma samples based on local characteristics, removing redundant information while preserving critical visual quality attributes, thereby reducing transmission and storage requirements without compromising perceived image quality.

The patent applies different filtering strengths and types to different regions of the image based on local characteristics. The adaptive loop filtering process analyzes local variance and applies stronger filtering in homogeneous regions while preserving detail in complex regions, achieving cost-effective compression that maintains quality where it matters most.

The patent extracts and processes only the essential visual information through selective filtering operations. The ALF and CCALF processes selectively modify chroma and luma samples based on local characteristics, removing redundant information while preserving critical visual quality attributes, thereby reducing transmission and storage requirements without compromising perceived image quality.

The patent dynamically adjusts filtering parameters such as filter strength, kernel size, and application regions based on local image characteristics like variance and gradient magnitude. This adaptive parameter adjustment allows the system to achieve better compression ratios by applying stronger filtering where appropriate while maintaining quality in critical regions.

The patent segments the filtering process into distinct stages: standard ALF for luma components and CCALF for chroma components. This segmentation allows each filtering type to be optimized independently with appropriate filter kernels and parameters, improving overall filtering accuracy while managing complexity through modular processing architecture.

The patent introduces an intermediate processing stage where luma filtering results are used to guide chroma filtering decisions in the CCALF process. This intermediary approach allows cross-component information to improve chroma quality without requiring complete reprocessing, thereby enhancing filtering accuracy while controlling computational complexity.

The patent segments the video content into hierarchical units (pictures, slices, coding blocks) and applies adaptive filtering at each level based on local characteristics. This segmentation enables targeted filtering that improves performance by adapting to local content variations while the hierarchical structure allows progressive refinement from coarse to fine levels.

The patent applies adaptive filtering selectively rather than uniformly across all blocks. By using thresholds and variance-based criteria, the system applies full adaptive filtering only where necessary, using simpler filtering or no filtering in regions where it would not provide significant benefit, thereby reducing signaling overhead while maintaining overall performance.