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雾天条件下的多尺度Retinex图像增强算法
引用本文:李菊霞,余雪丽.雾天条件下的多尺度Retinex图像增强算法[J].计算机科学,2013,40(3):299-301.
作者姓名:李菊霞  余雪丽
作者单位:(山西农业大学信息科学与工程学院 太谷030801) (太原理工大学计算机科学与技术学院 太原030024)
摘    要:在雾天条件下拍摄图像时,由于受到大气散射作用的影响,图像的颜色和对比度会出现退化现象。为了提高雾天图像的质量,提出一种改进的多尺度Retine雾天图像增强算法。首先采用幂次变换压缩图像动态范围;然后采用非线性变换对图像的高光区域进行抑制;最后采用反锐化掩模滤波消除图像模糊,增强雾天图像细节信息,并采用多幅雾天图像对算法性能进行仿真测试。仿真结果表明,改进多尺度Rctinc的雾天图像增强算法较好地解决了传统Retine算法存在的不足,加快了雾天图像增强的运行速度,使得雾天图像更加清晰化,获得了更优的视觉效果。

关 键 词:雾天图像,图像增强,色彩恒常理论,去雾

Enhance Algorithm for Fog Images Based on Improved Multi-scale Retinex
Affiliation:(College of Information Science and Engineering,Shanxi llgricultural University,Taigu 030801,China)(College of Computer Science and Technogy, Taiyuan University of Technology, Taiyuan 030024,China)
Abstract:When images are shot in fog circumstances, the color and contrast of fog images appear degrade phenomenon.In order to improve the quality of fog image, this paper proposed a fog image enhancement method based on improved multi-scale Retinex algorithm. Firstly, the dynamic range of image was compressed by the power transform, and then nonlinear transform was used to suppress the high light area of image,finally the unsharp mask filtering was used to eliminate fuzzy to enhance the detail information of fog image,and a few fog images were used to test the performance of the proposed algorithms. The simulation results show that the proposed algorithm solves the shortcomings of traditional Retinex algorithms, accelerates the speed of fog image enhancement, and the fog image is more clearly, so it can obtain better visual effect
Keywords:Fog image  Image enhancement  Retinex  Defog
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