[1]马康,崔子冠,干宗良,等. 基于图像融合策略的Retinex背光图像增强算法[J].计算机技术与发展,2017,27(08):73-78.
　MA Kang,CUI Zi-guan,GAN Zong-liang,et al. Backlight Image Enhancement Algorithm of Retinex Based on Image Fusion Strategy[J].,2017,27(08):73-78.
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 基于图像融合策略的Retinex背光图像增强算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年08期
页码:
73-78
栏目:
智能、算法、系统工程
出版日期:
2017-08-10

文章信息/Info

Title:
 Backlight Image Enhancement Algorithm of Retinex Based on Image Fusion Strategy
文章编号:
1673-629X（2017)08-0073-06
作者:
 马康; 崔子冠; 干宗良; 唐贵进; 刘峰
 南京邮电大学 通信与信息工程学院；;南京邮电大学 江苏省图像处理与图像通信重点实验室
Author(s):
 MA Kang; CUI Zi-guan; GAN Zong-liang; TANG Gui-jin; LIU Feng
关键词:
 ; Retinex ; 背光图像增强; 权重图; 融合策略
Keywords:
 ; Retinex; backlight image enhancement; weight maps; fusion strategy
分类号:
TP301.6
文献标志码:
A
摘要:
 Retinex是一种基于人类视觉的亮度和颜色感知的模型,在图像增强领域有着广泛的应用.背光作为常见的场景,使得拍摄到的图像存在暗区域不清晰、信息丢失等问题,影响图像的进一步分析和识别.为了提高对这类图像的增强效果,提出了一种基于图像融合策略的Retinex背光图像增强算法.该算法通过原始图像获取白平衡和增强图像,进行颜色校正和对比度增强,再分别对这两幅图像求其权重图以实现拉普拉斯金字塔融合,从而得到增强图像.权重图突显了背光区域的细节信息,与融合技术相结合,可有效提高背光区域的增强效果,获得对比度高、色彩丰富的增强图像.实验结果表明,与已有方法相比,所提出的图像增强算法能够更好地保留图像的细节信息,有效提高背光图像的对比度和清晰度.
Abstract:
 Retinex is a model of brightness and color perception based on human vision,which has wide applications in the field of image enhancement.As a common scene,backlight could make captured images blur in their dark areas,loss of information and others,which could impact further analysis and detection on the image.In order to improve the enhancement effect of such images,backlight image enhancement algorithm using Retinex based on image fusion strategy is proposed.It gets both the white balance and enhanced images by original image to carry on color correction and contrast enhancement.Then two images are achieved weight maps to implement Laplacian pyramid fusion for enhanced image.Weights maps highlights the details of the backlight region,which can effectively raise the enhancement effect of backlight area combined with fusion technology and acquire identified images with high contrast and ample hues.Compared with other existing methods,experimental results show that the proposed algorithm has retained the details and promoted the contrast and definition of backlight image.

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更新日期/Last Update: 2017-09-21