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Colorization Based Image Coding by Using Local Correlation between Luminance and Chrominance

机译:利用亮度和色度之间的局部相关性的基于着色的图像编码

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摘要

Recently, a novel approach to color image compression based on colorization has been presented. The conventional method for colorization-based image coding tends to lose the local oscillation of chrominance components that the original images had. A large number of color assignments is required to restore these oscillations. On the other hand, previous studies suggest that an oscillation of a chrominance component correlates with the oscillation of a corresponding luminance component. In this paper, we propose a new colorization-based image coding method that utilizes the local correlation between texture components of luminance and chrominance. These texture components are obtained by a total variation regularized energy minimization method. The local correlation relationships are approximated by linear functions, and their coefficients are extracted by an optimization method. This key idea enables us to represent the oscillations of chrominance components by using only a few pieces of information. Experimental results showed that our method can restore the local oscillation and code images more efficiently than the conventional method, JPEG, or JPEG2000 at a high compression rate.
机译:近来,已经提出了一种基于着色的彩色图像压缩的新颖方法。用于基于着色的图像编码的常规方法趋向于丢失原始图像具有的色度分量的局部振荡。需要大量的颜色分配以恢复这些振荡。另一方面,先前的研究表明,色度分量的振荡与对应的亮度分量的振荡相关。在本文中,我们提出了一种新的基于着色的图像编码方法,该方法利用了亮度和色度的纹理分量之间的局部相关性。这些纹理成分是通过总变化规则化能量最小化方法获得的。通过线性函数对局部相关关系进行近似,并通过优化方法提取其系数。这个关键思想使我们能够仅使用几条信息来表示色度分量的振荡。实验结果表明,与传统方法JPEG或JPEG2000相比,我们的方法可以在较高的压缩率下更有效地恢复本地振荡并对图像进行编码。

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