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arXiv · 2508.08794

Region-Adaptive Video Sharpening via Rate-Perception Optimization

Yingxue Pang·Shijie Zhao·Mengxi Guo·Junlin Li·Li Zhang
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Abstract

Sharpening is a widely adopted video enhancement technique. However, uniform sharpening intensity ignores texture variations, degrading video quality. Sharpening also increases bitrate, and there's a lack of techniques to optimally allocate these additional bits across diverse regions. Thus, this paper proposes RPO-AdaSharp, an end-to-end region-adaptive video sharpening model for both perceptual enhancement and bitrate savings. We use the coding tree unit (CTU) partition mask as prior information to guide and constrain the allocation of increased bits. Experiments on benchmarks demonstrate the effectiveness of the proposed model qualitatively and quantitatively.

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Yingxue Pang, Shijie Zhao, Mengxi Guo, Junlin Li, Li Zhang. 2025-08-12. Region-Adaptive Video Sharpening via Rate-Perception Optimization. https://arxiv.org/abs/2508.08794

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