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基于区域直方图统计的灰度图像色彩传递方法
引用本文:赵源萌,王岭雪,金伟其,骆媛. 基于区域直方图统计的灰度图像色彩传递方法[J]. 北京理工大学学报, 2012, 32(3): 322-326
作者姓名:赵源萌  王岭雪  金伟其  骆媛
作者单位:北京理工大学光电成像技术与系统教育部重点实验室,北京,100081;北京理工大学光电成像技术与系统教育部重点实验室,北京,100081;北京理工大学光电成像技术与系统教育部重点实验室,北京,100081;北京理工大学光电成像技术与系统教育部重点实验室,北京,100081
基金项目:国家自然科学基金资助项目(60971010);国家教育部高等学校博士学科点专项科研基金资助课题(20070007022);北京理工大学全国百篇博士优秀论文育苗及奖励基金
摘    要:应用直方图统计法描述图像的区域纹理,提出基于区域直方图纹理描述的灰度图像色彩传递处理方法.为待彩色化处理的灰度图像选定适当的参考图像,并在去相关的对立色空间对两幅图像的亮度通道作线性变换.用直方图统计法描述的像素邻域纹理特征进行图像间的像素匹配,将匹配性最佳的参考图像像素的颜色值传递给相应灰度图像像素的颜色通道,将色彩传递结果图像转换回RGB空间显示.实验结果表明:该方法能够提高像素匹配的准确性,获得色彩自然感优于常规色彩传递方法的彩色化图像;该方法运算量较小,便于实际应用.

关 键 词:图像处理  灰度图像彩色化  色彩传递  纹理特征提取  直方图统计法
收稿时间:2010-09-20

A Color Transfer Method for Colorization of Grayscale Image Based on Region Histogram Statistics
ZHAO Yuan-meng,WANG Ling-xue,JIN Wei-qi and LUO Yuan. A Color Transfer Method for Colorization of Grayscale Image Based on Region Histogram Statistics[J]. Journal of Beijing Institute of Technology(Natural Science Edition), 2012, 32(3): 322-326
Authors:ZHAO Yuan-meng  WANG Ling-xue  JIN Wei-qi  LUO Yuan
Affiliation:Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China;Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China;Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China;Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing Institute of Technology, Beijing 100081, China
Abstract:A color transfer method for grayscale image colorization based on region histogram texture description is proposed in this article. First a suitable reference image is selected for the grayscale image to be colorized, and linear transformation was applied to the luminance channels of the two images in a de-correlated opponent color space. Then the pixels were matched between two images using pixel neighborhood texture features described by histogram statistics, and the color values of best matching reference image pixel were transferred to the corresponding chromatic channels of grayscale image pixel. Finally the color transferred image is transformed back to the RGB space to be displayed. The result shows that the proposed method has the advantages of high pixel matching accuracy and low computational complexity. The obtained colorized image has better natural colorful feeling than that from image using conventional color transfer methods.
Keywords:image processing  grayscale image colorization  color transfer  texture feature extraction  histogram statistical approach
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