Colorization-Based Compression Using Optimization
Colorization-Based Compression Using Optimization
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DOI：
10.1109/tip.2013.2253486
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发表时间：
2013-03
影响因子：
10.6
通讯作者：
S. Lee;Sang Wook Park;Paul Oh;M. Kang
中科院分区：
文献类型：
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作者：
S. Lee;Sang Wook Park;Paul Oh;M. Kang
在本文中，我们将基于彩色化的编码问题转化为一个优化问题，即L1最小化问题。在基于彩色化的编码中，编码器选择几个具有代表性的像素(RP)，将其色度值和位置发送到解码器，而在解码器中，通过彩色化方法重建所有像素的色度值。彩色化编码的主要问题是如何很好地提取RP，从而获得较好的压缩比和重建的彩色图像质量。通过将基于彩色化的编码表示为L1最小化问题，可以确保在给定彩色化矩阵的情况下，从最小化原始彩色图像和重建彩色图像之间的误差的意义上讲，所选择的RP集合成为最优集合。换句话说，对于固定的误差值和给定的彩色化矩阵，所选择的RP集合是可能的最小集合。我们还提出了一种构造彩色化矩阵的方法，以多尺度的方式对图像进行彩色化。这一点与所提出的RP提取方法相结合，允许我们选择非常小的RP集。实验表明，该方法的性能优于传统的基于彩色化的编码方法和JPEG2000压缩标准，在压缩比和重建彩色图像质量方面与JPEG2000标准相当。
In this paper, we formulate the colorization-based coding problem into an optimization problem, i.e., an L1 minimization problem. In colorization-based coding, the encoder chooses a few representative pixels (RP) for which the chrominance values and the positions are sent to the decoder, whereas in the decoder, the chrominance values for all the pixels are reconstructed by colorization methods. The main issue in colorization-based coding is how to extract the RP well therefore the compression rate and the quality of the reconstructed color image becomes good. By formulating the colorization-based coding into an L1 minimization problem, it is guaranteed that, given the colorization matrix, the chosen set of RP becomes the optimal set in the sense that it minimizes the error between the original and the reconstructed color image. In other words, for a fixed error value and a given colorization matrix, the chosen set of RP is the smallest set possible. We also propose a method to construct the colorization matrix that colorizes the image in a multiscale manner. This, combined with the proposed RP extraction method, allows us to choose a very small set of RP. It is shown experimentally that the proposed method outperforms conventional colorization-based coding methods as well as the JPEG standard and is comparable with the JPEG2000 compression standard, both in terms of the compression rate and the quality of the reconstructed color image.