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Correlation based universal image/video coding loss recovery

机译:基于相关性的通用图像/视频编码丢失恢复

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摘要

Coding artifacts are annoying in highly compressed signals. Most of the existing artifact reduction methods are designed for one specific type of artifacts, codecs, and bitrates, which are complex and exclusive for one type of artifact reduction. Since both the compressed image/video and the coding error contain information of the original signal, they are highly correlated. Therefore, we try to recover some lost data based on the correlation between the compressed signal and the coding error, and introduce a novel and universal artifact reduction method. Firstly, according to the spatial correlation among pixels, a pixel-adaptive anisotropic filter is designed to reconstruct the distorted signal. Next, a globally optimal filter is designed to further recover the coding loss. Experimental results demonstrate that within an extensive range of bitrates, the proposed method achieves about 0.8 dB, 0.45 dB, 0.3 dB, and 0.2 dB on average of PSNR improvement for JPEG, MPEG4, H.264/AVC, and HEVC compressed signals, respectively.
机译:编码伪像在高度压缩的信号中令人讨厌。现有的大多数减少伪像的方法都是针对一种特定类型的伪像,编解码器和比特率设计的,这些方法是复杂的,并且仅用于一种减少伪像的方法。由于压缩的图像/视频和编码错误均包含原始信号的信息,因此它们高度相关。因此,我们尝试基于压缩信号与编码误差之间的相关性来恢复一些丢失的数据,并介绍一种新颖且通用的减少伪像的方法。首先,根据像素之间的空间相关性,设计了一种像素自适应各向异性滤波器来重构失真信号。接下来,设计全局最优滤波器以进一步恢复编码损失。实验结果表明,在较大的比特率范围内,对于JPEG,MPEG4,H.264 / AVC和HEVC压缩信号,所提方法的PSNR平均改善分别约为0.8 dB,0.45 dB,0.3 dB和0.2 dB。 。

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