基于奇异向量分解的运动补偿残差自适应变换

Xiaoran Cao, Yun He
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引用次数: 13

摘要

视频编码标准常用离散余弦变换(DCT)对运动补偿残差进行变换。然而,残差与图像像素的相关性要弱得多,DCT并不是残差的最佳变换。本文提出了一种MC残差的自适应变换结构。与传统方法使用预定义的变换核不同,我们在预测块上应用奇异值分解(SVD),并使用特征向量矩阵作为变换核。实验表明,与传统方法相比,这种自适应变换具有更高的效率。在H.265/HEVC上实现时,比特率平均降低2.0%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Singular vector decomposition based adaptive transform for motion compensation residuals
Video coding standards commonly use discrete cosine transform (DCT) to transform the motion compensation (M-C) residuals. However, the MC residuals have much weaker correlation than image pixels, and DCT is not the optimized transform for them. In this paper, we propose an adaptive transform structure for MC residuals. Unlike traditional approaches which use a predefined transform core, we apply singular value decomposition (SVD) on the prediction block and use the eigenvector matrices as the transform core. Experiments show that this adaptive transform is more efficient compared with the traditional approach. An average 2.0% bit rate reduction is achieved when implemented on H.265/HEVC.
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