Metric-Driven Adaptive Video Encoding With Perceptual Entropy Filtering

The patent applies local quality by differentiating compression strength across different video regions. The system identifies perceptually important regions (such as areas with motion, edges, or high-frequency content) and applies lighter compression to these regions while applying stronger compression to perceptually less important regions. This is achieved through region-based quality metrics that evaluate local visual importance and adjust compression parameters accordingly, thereby reducing overall bandwidth consumption while preserving video quality in critical areas.

The patent implements dynamic adjustment of quantization parameters based on local perceptual importance. Instead of using uniform quantization parameters across the entire video frame, the system dynamically computes region-specific QP values by analyzing local video characteristics such as motion magnitude, edge density, and texture complexity. This dynamic approach allows the encoder to allocate bits more efficiently, using coarser quantization in less important regions and finer quantization in important regions, thereby improving encoding efficiency without sacrificing overall video quality.

The patent applies segmentation by dividing the video frame into multiple regions based on perceptual importance criteria. The system segments the video content into important regions (containing motion, edges, or fine details) and less important regions (smooth areas, low-frequency content). Different compression strategies are then applied to each segment, with important regions maintaining higher resolution and less important regions undergoing more aggressive compression. This segmentation approach enables bandwidth reduction while preserving visual quality in critical areas.