Pattern Detection Module for Video Encoding Region Quality

The patent applies local quality enhancement by identifying regions of interest (such as human faces) and applying different encoding parameters to these regions compared to non-interest regions. Specifically, the system detects skin-tone colors and determines regions containing human faces, then adjusts quantization parameters and bit allocation to preserve higher quality in these detected regions while using more aggressive compression in other areas, thereby resolving the contradiction between bandwidth reduction and picture quality maintenance.

The patent implements preliminary action by performing region detection and pattern recognition (such as identifying human faces through skin-tone color detection) before the actual encoding process. The system pre-processes the image to detect regions of interest and determines appropriate encoding parameters for these regions in advance, then applies these predetermined parameters during encoding. This approach maintains encoding speed while significantly improving region identification accuracy and edge preservation.

The patent directly addresses this contradiction by implementing local quality encoding. The system detects regions of interest (such as human faces identified through skin-tone color analysis) and applies different quantization parameters to these regions compared to non-interest regions. Specifically, lower quantization values (higher quality) are applied to detected regions of interest, while higher quantization values (lower quality) are used in other areas, thereby maintaining visual quality in important regions without uniformly increasing encoding complexity across the entire image.

The patent resolves this contradiction by applying local quality enhancement to regions of interest. The system identifies important regions (such as human faces through skin-tone color detection and pattern recognition) and allocates more bits and higher quality encoding to these specific regions, while using more aggressive compression in less important areas. This selective approach provides better perceived picture quality where users are most likely to notice differences, without proportionally increasing overall bandwidth consumption and memory usage.