Color recovery of black-and-white halftoned images via categorized color-embedding look-up tables

A new method of recovering the original colors of black-and-white (B&W) halftoned images with homogeneous dot patterns is proposed. The conventional inverse halftoning method, which uses a look-up table (LUT), can establish the relation between the halftoned patterns and the corresponding gray levels, while the conventional reversible color to gray conversion method can recover the original colors from a given color-embedded gray image. To accomplish our goal of original color recovery from B&W halftoned patterns, an approach of combining the conventional inverse halftoning and reversible color to gray conversion is presented in this paper. Differently from the conventional method of inverse halftoning via LUT, four LUTs categorized according to the red, green, blue, and gray reference colors are designed to more accurately map a specific B&W halftone pattern into the corresponding color-embedded gray level based on the observation that the shapes of the halftone patterns depend on input colors, thereby increasing the color recovery accuracy. Also, a color mapping method based on a linear regression which models the relation between the recovered colors and the original colors is introduced to adjust the initially recovered colors more closely to the original colors. Experimental results show that unknown original colors can be recovered from B&W halftoned images via the proposed method.     

颜色空间在图像彩色化处理中的应用分析

图像彩色化处理通常遵循颜色的局部相似性原则,选择适当的颜色空间是其重要问题。以能否实现颜色的亮度与色度分离为依据,将常用颜色空间分为颜色构成空间和颜色属性空间。考察了不同颜色空间中颜色分布的光滑程度,评估了各颜色空间在彩色化处理中的适用性。理论和实验结果表明,颜色属性空间更适用于彩色化处理。结合对彩色化本质的分析,引出了有关颜色空间选择的若干结论。     

An Ensemble Colorization Method

Colorization is a well established problem concerning recovering the potential colors of monochrome images. In the past decade several highly effective computer-assisted methods have been proposed for solving the colorizatlon problem, among which two methods achieved the state-of-the-art performance. The two methods are totally different＇s and each of them has its advantages and disadvantages. We propose an ensemble method unifying the two state-of-the-art methods to better exploit their advantages. Empirical results demonstrate the supe- riority of our ensemble method over using each of the two methods alone.     

Colorization coding based on iterative regression with major group priority

Colorization-based image coding is a new color image compression technique which compresses the color information of a color image into a small set of representative pixels (RP). The main issue in colorization-based coding is to design good RP extraction and colorization methods such that the compression rate and the quality of the reconstructed color become good. In this paper, we propose an iterative local regression method for RP extraction which takes the major group priority into account. It is shown that the problem of computing the RP can be formulated into a local regression problem. The local regions are obtained by performing a hierarchical image segmentation on the luminance channel both in the encoder and the decoder. Then the local regression parameters, i.e., the parameters that express the local relationship between the pixel values in the luminance channel and the chrominance channels are computed by taking the hierarchical structure into account. At the initial stage, the local regression parameters are calculated to fit the major tendency of the pixels in the segmented regions of the largest scale in the hierarchical structure. After that, additional regression parameters are extracted to reduce the remaining residual errors between the original color and the colors reconstructed by the previously computed local regression parameters. By repeating these steps, an RP set is extracted which can colorize the image in the decoder with sufficient detail. Experimental results show that the proposed algorithm performs better than the JPEG standard and conventional colorization-based coding methods in terms of the compression rate, PSNR and SSIM values.     

一种改进的基于过度分割的图像彩色化方法

黑白图像的彩色化是图像处理领域一个活跃的、有挑战性的研究课题。该文在总结图像彩色化方法的基础上,重点分析了Levin方法;针对这种方法处理大尺寸图像速度较慢的问题,提出先对图像进行过度分割,再以区域为基本单元进行彩色化的方案。实验表明,该方法能够在几乎不影响彩色化效果的前提下,显著提高处理大尺寸图像的速度。     

场景线稿动漫效果的自动上色算法

场景线稿具有线条语义多样化的特点,直接应用现有的人像线稿图自动上色算法对其着色容易出现上色错误或棋盘效应等结果失真的现象.针对上述问题,文中提出动漫效果自动上色算法.基于条件生成对抗网络,改进和增强人像线稿图自动上色算法中常用的U型网络(U-Net)生成器的结构,设计双层信息抽取的生成器网络(DIEU-Net),自动完成场景线稿到动漫效果的上色.DIEU-Net设计用于抽取场景线稿浅层显著信息的双卷积子模块(IESS).构建双层IESS与残差结构的集成模块,插入生成器的不同阶段,增强网络在与线稿关联的颜色、位置等重要特征上的全域学习能力,缓和网络加深带来的梯度消失等网络退化问题.同时采用“卷积+上采样”操作替换U-Net生成器中原有的反卷积操作,抑制生成结果中棋盘效应的发生.实验表明,文中算法能较好地克服结果失真的问题,上色效果合理、自然,具有较好的应用推广性,可应用于多种类型景物线稿图的动漫上色.     

A colorization algorithm based on local MAP estimation

This paper presents a colorization algorithm which adds color to monochrome images. In this paper, the colorization problem is formulated as the maximum a posteriori (MAP) estimation of a color image given a monochrome image. Markov random field (MRF) is used for modeling a color image which is utilized as a prior for the MAP estimation. The MAP estimation problem for a whole image is decomposed into local MAP estimation problems for each pixel. Using 0.6% of whole pixels as references, the proposed method produced pretty high quality color images with 25.7-32.6 dB PSNR values for eight images.     

Colorization in YCbCr color space and its application to JPEG images

This paper presents a colorization method in YCbCr color space, which is based on the maximum a posteriori estimation of a color image given a monochrome image as is our previous method in RGB color space. The presented method in YCbCr space is much simpler than that in RGB space and requires much less computation time, while both methods in YCbCr and RGB space produce color images with comparable PSNR values. The proposed colorization in YCbCr is applied to JPEG compressed color images aiming at better recovery of downsampled chrominance planes. Experimental results show that colorization in YCbCr is usually effective for quality improvement of JPEG color images.     

基于不平度颜色混合的图像彩色化方法

黑白图像的彩色化是图像处理领域一个活跃的、有挑战性的研究课题。该文在总结图像彩色化方法的基础上,提出了一种新型的、基于不平度的颜色混合方法。实验表明,该方法能够大大简化对初始着色的要求,并且达到很好的彩色化效果。