Image decolorization is to transform a color image into a grayscale image with the preserved contrast and consistent details. It is an important tool in image processing and realistic applications, such as monochrome printing and e-ink display. In this paper, we propose a novel contrast preserving method for image decolorization. Our main contribution is threefold: Firstly, we define a new contrast feature for a color image which combine the correlated information among R, G and B channels with the color contrast in each channel. Secondly, we propose to use the weighted normalized L1 norm to measure the distance between the grayscale image and the color image contrast features, and formulate an constrained optimization problem. Finally, we utilize a discrete searching solver to solve the optimization problem efficiently. The proposed decolorization method is good at preserving low contrast as well as high contrast structures in the color image. The objective and subjective evaluation on three benchmark datasets demonstrates that our decolorization method is effective and competitive with some state-of-the-art decolorization methods.

图像脱色是将彩色图像转换为保留对比度和一致细节的灰度图像。它是图像处理和现实应用中的重要工具，例如单色打印和电子墨水显示。在本文中，我们提出了一种新的图像去色对比度保持方法。我们的主要贡献有三方面：首先，我们为彩色图像定义了一个新的对比度特征，它将 R、G 和 B 通道之间的相关信息与每个通道的颜色对比度相结合。其次，我们建议使用加权归一化L1范数来衡量灰度图像与彩色图像对比度特征之间的距离，并制定一个约束优化问题。最后，我们利用离散搜索求解器来有效地解决优化问题。所提出的脱色方法擅长保留彩色图像中的低对比度和高对比度结构。对三个基准数据集的客观和主观评估表明，我们的脱色方法是有效的，并且与一些最先进的脱色方法相比具有竞争力。