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基于多尺度几何分析的雾天图像清晰化算法

Foggy Image Sharpening Algorithm Based on Multi-Scale Geometric Analysis

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摘要

提出了一种基于非下采样Contourlet变换(NSCT)的雾天图像清晰化算法,将雾天图像映射到HIS彩色空间,对亮度分量H、饱和度分量S分别处理。采用NSCT处理亮度分量H,对含有大多数能量的低频分量取反,再进行改进的单尺度Retinex算法处理,将再次取反后的图像与直接进行改进的单尺度Retinex算法处理的低频分量线性叠加;采用一种快速双边滤波器对包含图像大多数线性细节的高频分量进行处理;对处理后的高低频分量进行NSCT逆变换,得到处理后的亮度分量。对饱和度分量S进行颜色拉伸,实现颜色补偿;将处理后的各分量图像反向映射到RGB颜色空间,得到清晰化后的雾天图像。实验结果表明,该算法可以获得较好的浓雾图像细节及颜色保真度,与其他算法相比,图像的标准差、信息熵、峰值信噪比都有所提高。

Abstract

A foggy image sharpening algorithm based on nonsubsampled Contourlet transformation (NSCT) is proposed. The foggy image is mapped to the HIS color space, and the luminance component H and the saturation component S are processed respectively. The NSCT is used to process the luminance component H. The low-frequency component containing most energy is negated and then processed by the improved single-scale Retinex algorithm. The image is negated again and is superposed linearly with the low-frequency components processed by the improved single-scale Retinex algorithm directly. A fast bilateral-filter is applied to the high-frequency components that contain most of the linear details of the image. Then the two processed components are inversely transformed by NSCT, and the processed luminance components are obtained. Finally, the saturation component S is linearly stretched to achieve color compensation. The processed image of each component is mapped backward to the RGB color space to get a clear foggy image. The experimental results show that the proposed algorithm achieves good results of the details and color fidelity for the foggy image. Compared with other algorithms, the standard deviation, information entropy and peak signal to noise ratio are improved.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP751.1

DOI:10.3788/lop55.111009

所属栏目:图像处理

基金项目:国家自然科学基金(61562057,61663021,61761027,51669010)、教育部长江学者和创新团队发展计 划(IRT_16R36)、甘肃省教育厅科技计划(2017D-08)、甘肃省自然科学基金(17JR5RA101)、甘肃省“十三五”教育科学规划课题(GS[2016]GHB0217)、甘肃省创新创业教育改革项目(2017-44)

收稿日期:2018-04-26

修改稿日期:2018-05-26

网络出版日期:2018-06-06

作者单位    点击查看

郭瑞:兰州交通大学电子与信息工程学院, 甘肃 兰州730070
党建武:兰州交通大学电子与信息工程学院, 甘肃 兰州730070
沈瑜:兰州交通大学电子与信息工程学院, 甘肃 兰州730070
刘成:兰州交通大学电子与信息工程学院, 甘肃 兰州730070

联系人作者:沈瑜(912064869@qq.com)

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引用该论文

Guo Rui,Dang Jianwu,Shen Yu,Liu Cheng. Foggy Image Sharpening Algorithm Based on Multi-Scale Geometric Analysis[J]. Laser & Optoelectronics Progress, 2018, 55(11): 111009

郭瑞,党建武,沈瑜,刘成. 基于多尺度几何分析的雾天图像清晰化算法[J]. 激光与光电子学进展, 2018, 55(11): 111009

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