A Color to Grayscale Conversion Considering Local and Global Contrast
A Color to Grayscale Conversion Considering Local and Global Contrast
复制标题
DOI：
10.1007/978-3-642-19282-1_41
复制
发表时间：
2010-11
期刊：
影响因子：
--
通讯作者：
J. Kuk;Jaeheong Ahn;N. Cho
中科院分区：
文献类型：
--
作者：
J. Kuk;Jaeheong Ahn;N. Cho
为了将彩色图像转换为视觉上可信的灰度图像，本文同时考虑了全局对比度和局部对比度。对比度用梯度场来度量，当灰度图像的梯度场与原始彩色图像的梯度场(称为目标梯度场)越接近时，能量函数的取值越小。为了将局部和全局对比度都编码到能量函数中，目标梯度场由两种边缘构成：一种边缘将每个像素连接到相邻像素，另一种边缘将每个像素连接到预定的地标像素。虽然我们可以在最小二乘意义下得到能量最小化的精确解，但我们也提出了一种通过逼近能量函数来实现大图像转换的快速实现方法。然后将问题归结为在标准的4邻域系统上从修正的梯度场重建灰度图像，这可以很容易地用快速的二维泊松求解器来解决。在实验中，提出的方法在不同的图像上进行了测试，结果表明，该方法比现有的方法给出了更可信的结果。
For the conversion of a color image to a perceptually plausible grayscale one, the global and local contrast are simultaneously considered in this paper. The contrast is measured in terms of gradient field, and the energy function is designed to have less value when the gradient field of the grayscale image is closer to that of original color image (called target gradient field). For encoding both of local and global contrast into the energy function, the target gradient field is constructed from two kinds of edges : one that connects each pixel to neighboring pixels and the other that connects each pixel to predetermined landmark pixels. Although we can have exact solution to the energy minimization in the least squares sense, we also present a fast implementation for the conversion of large image, by approximating the energy function. The problem is then reduced to reconstructing a grayscale image from the modified gradient field over the standard 4-neighborhood system, and this can be easily solved by the fast 2D Poisson solver. In the experiments, the proposed method is tested on various images and shown to give perceptually more plausible results than the existing methods.