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作 者:罗浩[1] 仲佳嘉 李祥 LUO Hao;ZHONG Jiajia;LI Xiang(College of Applied Science,Jiangxi University of Science and Technology,Ganzhou 341000,Jiangxi Province,China;Ganzhou Electric Power Supply Branch Company,Jiangxi Eletric Power Co.,Ltd,State Grid Corporation of China,Ganzhou 341000,Jiangxi Province,China)
机构地区:[1]江西理工大学应用科学学院,江西赣州341000 [2]国网江西省电力有限公司赣州供电分公司,江西赣州341000
出 处:《吉林大学学报(理学版)》2019年第2期369-374,共6页Journal of Jilin University:Science Edition
基 金:国家自然科学基金青年科学基金(批准号:11704164)
摘 要:针对传统基于多尺度Retinex的单幅彩色图像增强算法,进行图像增强时未考虑亮度分量和局部对比度,导致图像增强未达到最佳尺度值,获取的增强图像存在失真、带有雾膜的问题,提出一种基于改进多尺度Retinex的单幅彩色图像增强算法.首先采用高斯环境函数对3种灰度图像实施卷积并进行灰度纠正,将3种纠正灰度后的图像合并,获取初步单幅彩色图像增强结果;然后改进多尺度Retinex的单幅彩色图像增强算法,增强单幅彩色图像像素的平均亮度;最后通过非线性函数对亮度增强后的彩色图像实施局部对比度增强处理,用线性调整方法恢复局部对比度增强后的图像颜色,以获取最佳单幅彩色图像的图像增强结果.实验结果表明,该算法可获得亮度和对比度均较好的单幅彩色图像增强结果.Aiming at the problem that the traditional single color image enhancement algorithm based on multi-scale Retinex did not consider the brightness component and local contrast when image enhancement was performed,which led to the image enhancement not reaching the optimal scale value,and the obtained enhanced image had the distortion and fog film,we proposed a single color image enhancement algorithm based on the improved multi-scale Retinex.Firstly,the Gaussian environment function was used to convolve the three grayscale images and perform grayscale correction.The three corrected grayscale images were combined to obtain a preliminary single color image enhancement result.Secondly,we improved multi-scale Retinex single color image enhancement algorithm to enhance the average brightness of single color image pixels.Finally,local contrast enhancement processing of color image after brightness enhanced was performed by nonlinear function,and image color after local contrast enhancement was restored by linear adjustment method to obtain the best image enhancement results of single color image.The experimental results show that the proposed algorithm can obtain single color image enhancement results with good brightness and contrast.
关 键 词:多尺度RETINEX算法 图像增强 亮度分量 对比度
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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