标题： 频率辅助的自适应锐化方案考虑比特率和质量的权衡 显示英文标题

标题： Frequency-Assisted Adaptive Sharpening Scheme Considering Bitrate and Quality Tradeoff

摘要： 锐化是一种广泛采用的技术，用于提高视频质量，可以有效强调纹理并减轻模糊。 然而，增加锐化级别会带来更高的视频比特率，导致服务质量（QoS）下降。 此外，视频质量并不一定随着锐化级别的增加而改善，这会导致过度锐化等问题。 显然，有必要弄清楚如何在适当锐化级别下提升视频质量，同时有效控制带宽成本。 因此，本文提出了一种新的基于频率的锐化级别预测模型（FreqSP）。 我们首先将每个视频标记为与最佳比特率和质量权衡相关的锐化级别作为真实值。 然后以未压缩的源视频作为输入，所提出的FreqSP利用复杂的CNN特征和高频成分来估计最佳锐化级别。 大量实验证明了我们方法的有效性。 显示英文摘要

摘要： Sharpening is a widely adopted technique to improve video quality, which can effectively emphasize textures and alleviate blurring. However, increasing the sharpening level comes with a higher video bitrate, resulting in degraded Quality of Service (QoS). Furthermore, the video quality does not necessarily improve with increasing sharpening levels, leading to issues such as over-sharpening. Clearly, it is essential to figure out how to boost video quality with a proper sharpening level while also controlling bandwidth costs effectively. This paper thus proposes a novel Frequency-assisted Sharpening level Prediction model (FreqSP). We first label each video with the sharpening level correlating to the optimal bitrate and quality tradeoff as ground truth. Then taking uncompressed source videos as inputs, the proposed FreqSP leverages intricate CNN features and high-frequency components to estimate the optimal sharpening level. Extensive experiments demonstrate the effectiveness of our method.