Fog Removal from Video Sequences Using Contrast Limited Adaptive Histogram Equalization

The video sequences degraded by fog suffer from poor visibility. In this paper, we present a contrast limited adaptive histogram equalization (CLAHE)-based method to remove fog. CLAHE establishes a maximum value to clip the histogram and redistributes the clipped pixels equally to each gray level. It can limit the noise while enhancing the contrast. First, the background image is extracted from the video sequence. And then the moving pixels are estimated and bounded into foreground images. Second, the foreground and background images are defogged respectively by CLAHE. Third, the foreground and background images are fused into the new frames. Finally, the defogged video sequence is obtained. We experiment with a video sequence degraded by fog to evaluate the effectiveness of our method. And the histogram statistics are applied in comparison with traditional method. The results show that our method is more effective than traditional method. In addition, our method can fill the requirement of real-time.