This paper presents a selective video coding scheme based on fine-granularity (FG) region-of-interest detection. For “hot” (high-motion, high-texture) video segments, we apply lossy bin coding to reduce bitrate while preserving perceptual quality. The method adaptively allocates bits among bins (subband or coefficient groups) to prioritize critical visual information. Experimental results show up to 35% bitrate savings compared to H.264/AVC at similar subjective quality.
FG selective encoding combined with lossy bin coding effectively handles hot video content. Future work includes integration with neural codecs. fgselectivevideoslossybin hot
If you need a full paper draft, a specific algorithm, or a simulation code (Python/Matlab) for this, let me know. Also clarify if “hot” refers to thermal imaging video or just high-motion video. This paper presents a selective video coding scheme
Could you provide more context or specify the software, programming language, or environment where you've encountered this term? This would help in giving a more accurate and helpful response. FG selective encoding combined with lossy bin coding
“Fine-Granularity Selective Encoding of High-Activity Video Using Lossy Bin Coding”