单幅图像去雾算法

目前图像去雾算法研究大多忽略颜色失真问题，特别是存在高亮度区域的图像复原，针对如何同时保证图像细节与颜色信息问题，本文提出一种基于双边滤波的单幅图像去雾算法。首先，利用巴特沃斯低通滤波直接估计背景空气光，避免对不同尺寸的图像以及对图像不同的分块所引起的误差；然后，利用双边滤波估计大气光幕，代替He算法中soft matting过程，以获得优化的透射图，提高计算效率；最后，在HSV空间利用亮度增益函数对复原图像进行颜色校正，最终获得复原图像。仿真实验通过与几种经典算法的比较验证本文算法在色彩保真度及算法鲁棒性等方面的有效性。

Single Image Haze Removal Algorithm

At present, most of the haze removal algorithms ignore the color distortion problem, especially in areas with high brightness. This paper proposes a single image haze removal algorithm using the bilateral filtering to ensure the image detail and color information at the same time. First of all, the Butterworth low-pass filter is used to directly estimate the background air light in order to avoid the errors caused by different sizes of images and different blocks of images. Then, the bilateral filter is used to estimate the atmospheric light curtains instead of the soft matting process in He’s algorithm to obtain the optimum transmission diagram and improve the computational efficiency. Finally, the brightness gain function is used to restore color in the HSV space. Compared with several classical algorithms, simulation experimental results verify the color calibration and the effectiveness of the proposed algorithm.