基于区域分割的雾天图像增强算法

由于受雾天光亮条件的限制,雾天拍摄的图像一般都有比较严重的图像降质;针对雾天图像的退化现象,提出了一种基于区域分割的雾天图像增强方法;该方法无需依据大气模型,而是采取基于边缘检测的区域分割方法首先将图像平坦区域提取出来,然后对非平坦区域进行局部直方图均衡化处理;同时,为防止区域边界效应的产生,通过距离变换进行渐变处理,最后对获取的图像进行信息融合,进一步提高图像质量;通过实验分析和验证,证实了该算法能有效地改善雾天图像的退化现象和提高图像清晰度.

Enhancement Algorithm of Misty Image Based on Region Segmentation

Since existing the lighting limitation of foggy weather, images taken in fogs ordinarily have the comparatively serious degradation. According to the degraded phenomenon of images, a new method based on the Region Segmentation for enhancing the misty images is proposed. It does not need atmospheric model and just performs on the image, the flat region firstly is segmented from the image by edge detection, and the uneven region is processed using local histogram equalization. At the same time, the image feathering process is adopted to resolve the problem of edge effect in the flat region, and images are fused to improve the quality of image. The experiment shows that the method proposed above is very effective to improve the degradation of images and can enhance the clearness of images.