基于暗原色的雾天图像增强算法
毕业论文关键字 暗原色先验 图像去雾 C语言 大气散射模型
Title Single Image Haze Removal Using Dark Channel Prior Abstract Under foggy conditions, due to outdoor scenes affected by fog, the image contrast of image from sensor drop and have loss of detail in the image scene, so the image becomes blurred, and the subsequent image processing and analysis has brought great difficulties. Therefore, image restoration technology research under foggy conditions can increase the image contrast and sharpness, improve the quality of the image, which for computer vision system to ensure reliable and stable work in inclement weather, with a theoretical and practical value is very important. Currently, there are two main directions for recovery technology research of foggy image. One direction is the processing from the perspective of image enhancement, and another physical imaging model is based on a foggy image processing. Although Image enhancement method can improve the visual effect to some extent, but usually can not effectively remove the impact of fog. In contrast, the method of the imaging model-based has the clear physical interpretation, with better results and universality. Currently, the studies of image defogging physical imaging model-based approach will be more and more. The paper is based on C language , atmospheric scattering model and a priori theory of dark colors to achieve the work to fog foggy color image processing more effective. Remove the effects of haze, enhance image contrast, increase visibility and achieve foggy images quickly and effectively addressed. Keywords: Dark Channel prior; Dehazing ; C ;Atmospheric scattering model;
目 次
1 绪论 . 1
1.1 课题背景 .. 1
1.2研究意义 2
1.3 国内外现状 2
1.4 论文主要内容 . 3
2 相关理论及技术基础 .. 5
2.1雾天图像降质原因 . 5
2.2暗原色先验 . 6
2.3滤波技术 6
2.4大气散射退化模型 . 7
2.5基于 opencv下的 C语言编程 . 8
3 基于暗原色的雾天图像增强算法 . 12
3.1暗原色先验去雾 .. 12
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