有雾图像和沙尘图像增强算法

针对有雾图像和沙尘图像存在色差、 清晰度较差的问题, 提出一种有雾图像和沙尘图像增强算法. 首先, 在Lab颜色空间用灰度世界算法解决沙尘图像的色差问题, 将调整色差后的沙尘图像与有雾图像转换到HSV颜色空间, 分别提高图像的饱和度和对比度; 其次, 用Laplace算子检测图像的模糊程度, 对于模糊度较高的图像, 用基于加权最小二乘滤波算法去除图像的模糊特征, 进一步提高图像可见度; 最后, 与现有的去雾算法和沙尘增强算法进行对比实验. 实验结果表明, 该算法可以更好地恢复图像的色彩, 并有效提高图像清晰度.

Enhancement Algorithm of Fog Image and Dust Image

Aiming at the problem of chromatic aberration and poor definition between fog image and dust image, we proposed an enhancement  algorithm of fog image and dust image. Firstly, the grayscale world algorithm was used to solve the chromatic aberration problem of dust image in Lab color space, the dust image and fog image after adjusting the chromatic aberration were converted to HSV color space to improve the saturation and contrast of the image respectively. Secondly, the Laplacian operator was used to detect the blur degree of the image. For the image with high blur degree, the weighted least squares filtering algorithm was used to remove the fuzzy features and further improve the visibility of the image. Finally, a comparative experiment was carried out with the existing fog removal algorithm and dust enhancement algorithm. The experimental results show that the algorithm can better restore the color of the image and effectively improve the image definition.