Image Haze Removal of Wiener Filtering Based on Dark Channel Prior

Abstract

If we use the image haze removal of dark channel prior, we're prone to color distortion phenomenon for some large white bright area in the image. Aimed at these problems, this paper presents an image haze removal of wiener filtering based on dark channel prior. The algorithm is mainly to estimate the median function in the use of the media filtering method based on the dark channel, to make the media function more accurate and combine with the wiener filtering closer. So that the fog image restoration problem is transformed into an optimization problem, and by minimizing mean-square error a clearer, fogless image is finally obtained. Experimental results show that the proposed algorithm can make the image more detailed, the contour smoother and the whole image clearer. In particular, this algorithm can recover the contrast of a large white area fog image. The algorithm not only compensates for the lack of dark channel prior algorithm, but also expands the application of dark channel prior algorithm and shortens the running time of the image algorithm.