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摘要当下，图像由于蕴含有大量的信息，是我们得到信息必不可少的来源。然而由于越来越多的雾霾天气的影响，使得通过现有成像系统获得的图像发生了严重的退化，这很大程度上降低了它的使用价值。因此，研究雾天退化图像的增强处理方法是十分必要的。21851
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本文首先在介绍了视觉成像的基本原理的基础上进一步讨论了在雾天图像的退化机理,并简要介绍了两种图像复原的经典方法。然后从图像增强的角度出发，研究了两种直方图均衡化的方法，即全局直方图均衡化与局部直方图均衡化，并提出了一种改进算法，接下来介绍了同态滤波法。最后重点介绍了基于Retinex理论的图像增强法，随后分别探讨了全局Retinex、SSR、MSR与MSRCR算法，以及综合了全局Retinex和MSR的改进算法。仿真结果表明这几种算法相较直方图均衡化和同态滤波而言，处理效果更佳，能更为有效地对退化图像进行增强。
关键词：图像退化 图像增强 直方图均衡化 同态滤波 Retinex算法
毕业论文设计说明书（论文）外文摘要
Title The Research of Foggy Iamge Enhancement Processing
Abstract
Nowadays, image ,which contains a large amount of information, became an important source of information. However, due to the influence of more and more fog and haze,the image got through the existing imaging system deteriorates seriously, resulting in the low quality. Therefore, studying the processing method of fog degradation image is of pratical significance.
This paper first briefly introduced two kinds of method of image restoration based on the visual image and the degradation mechanism of foggy images. Then from the view of image enhancement, two kinds of histogram equalization method are discussed, the global histogram equalization and local area histogram equalization, then proposed an improved algorithm. The homomorphic filtering method is discussed as well. Finally, the image enhancement method that based on Retinex theory is recommended, discussing the Global Retinex, SSR, MSR and MSRCR algorithm respectively, then proposed an improved algorithm using both global Retinex and MSR. The simulation results show that the these kinds of algorithm are better than the histogram equalization and homomorphic filtering, and they can enhance the degraded image effectively.
Keywords image degradation image enhancement histogram equalization homomorphic filtering Retinex algorithm
目 录
1 绪论 1
1.1 研究背景 1
1.2 研究现状 2
1.3 论文研究工作和内容安排 3
2 视觉成像原理及图像退化模型 5
2.1 视觉成像原理 5
2.2 图像退化模型 5
2.3 经典图像复原算法 6
3 直方图均衡化 9
3.1 全局直方图均衡化 9
3.2 局部直方图均衡化 12
3.3 本章小结 15
4 同态滤波 17
4.1 基本原理 17
4.2 算法介绍 17
4.3 结果分析 19
4.4 本章小结 20
5 基于Retinex的雾天图像增强算法 21
5.1 Retinex理论 21
5.2 全局 Retinex 算法 22
5.3 SSR算法 24
5.4. MSR算法 29
5.5 MSRCR算法 31
5.6 综合全局与MSR的算法改进 33
5.7 本章小结 35