High-frequency guided CNN for video compression artifacts reduction

Li Yu, Wenshuai Chang, Qingshan Liu, M. Gabbouj
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引用次数: 1

Abstract

In this paper, we propose a high-frequency guided CNN for video compression artifacts reduction. In the proposed method, high frequency component in Y channel is extracted and used to guide the quality enhancement of all Y, U, V channels. As high frequency component contains the edge and contour information of the objects in the image, which is of vital importance to both subjective and objective quality. In general, the proposed method consists of two modules: the high frequency guidance module and the quality enhancement module. The high-frequency guidance module uses multiple octave convolutions to extract the high-frequency component in Y channel and then fuse it into the features of Y, U, and V channels. While in the quality enhancement module, multiple CNN residual blocks are used for the quality enhancement of Y, U, and V channels. The proposed method was integrated into both HM-16.22 and VTM-16.0. The results on the JVET test sequence under All Intra configuration shows the effectiveness of the proposed method. Compared with HEVC, the proposed method achieves the average BD-rate reductions of -12.3%, -22.7% and -23.5% for Y, U and V channels respectively. Compared with VVC, the average BD-rate reductions are -6.7%, -12.3% and -13.2% correspondingly.
高频导引CNN用于视频压缩伪影的减少
在本文中,我们提出了一种用于减少视频压缩伪影的高频引导CNN。该方法提取Y通道中的高频分量,用于指导Y、U、V通道的质量增强。由于高频分量包含了图像中物体的边缘和轮廓信息,对图像的主客观质量都至关重要。总的来说,该方法由两个模块组成:高频制导模块和质量增强模块。高频制导模块使用多个倍频卷积提取Y通道的高频分量,然后将其融合到Y、U、V通道的特征中。而在质量增强模块中,使用多个CNN残差块对Y、U、V通道进行质量增强。将该方法集成到HM-16.22和VTM-16.0中。所有Intra配置下JVET测试序列的结果表明了该方法的有效性。与HEVC相比,该方法在Y、U和V通道上的平均bd率分别降低了-12.3%、-22.7%和-23.5%。与VVC相比,BD-rate的平均降幅分别为-6.7%、-12.3%和-13.2%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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