基于MSR理论的交通图像去雾霾方法

基于MSR理论的交通图像去雾霾方法
李长领;宋裕庆;刘晓锋
【期刊名称】《计算机应用》
【年(卷),期】2015(000)0z2
【摘要】Due to the frequent fog and haze, it becomes more and more difficult for trffic departments to collect high-quality road images. In order to improve the image quality, a novel method to remove haze from traffic images based on Multi-Scale Retinex ( MSR) theory was proposed. Firstly, the original haze image and its inverse image were transformed respectively by an MSR transformation; Secondly, a linear stretching transformation and an exponential transformation were applied; At last the two resulted images were linearly summed with different weights. The experiments were conducted on a large number of traffic images with haze. The experimental results demonstrate that the proposed method performs better than traditional haze removal methods, such as exponential transformation, histogram equalization, and MSR. It can effectively enhance the contrast and fidelity of image, and balance between the distant view and close shot as well.%为解决因雾霾天气导致的图像质量退化问题，减轻交通部门对交通视频图像的监测难度，提出了一种基于多尺度
Retinex( MSR)的图像去雾霾算法。

基于MSR理论，通过将原雾霾图像及其反转图像分别进行MSR变换，然后进行线性拉伸和幂次变换，最后将两幅图像处理结果加权线性相加，达到图像去雾的目的。

通过对大量雾霾交通图像进行实验，实验
结果表明此算法对雾霾图像的处理效果要好于幂次变换、直方图均衡化、MSR等图像去雾霾算法。

提出图像去雾霾算法，在MSR算法的基础上进行了改进，实验结果表明该方法不仅有效地增强了图像的对比度和保真度，而且还使图像远景与近景得到一定的平衡。

【总页数】4页(P234-237)
【作者】李长领;宋裕庆;刘晓锋
【作者单位】天津职业技术师范大学汽车与交通学院，天津300222;天津职业技术师范大学汽车与交通学院，天津300222;天津职业技术师范大学汽车与交通学院，天津300222
【正文语种】中文
【中图分类】TP751.1
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