针对目前去雾图像质量客观评价方法少和已有评价方法存在局限性等问题,提出一种去雾图像的 客观质量评价新方法。针对去雾图像中存在的Halo效应,采用边缘加权结构相似性测度的方法,将雾 化图像和去雾图像的整体轮廓信息与局部纹理细节信息加权来描述图像的结构相似度。从人类视觉感 知的角度出发,定义了图像归一化灰度差,用来描述图像的亮度。将彩色图像转换到HSV颜色空间, 利用S分量的信息熵和直方图相似度来描述图像的色彩还原能力。最后综合边缘加权结构相似性测度、 图像归一化灰度差和色彩加权还原度建立去雾图像质量评价模型,并进行客观评价和比较。实验结果表明, 与已有评价方法相比,所提出的评价方法能够获得与主观感受一致的结果,并具有较好的有效性和可靠性。

Since there is lack of methodology to assess the performance of defogging method and the existing assessment methods have some limitations, a new objective quality assessment method for defogged images is proposed. For the halo artifacts, an edge-weighted structural similarity index is adopted to assign different weights to contour correlation and local texture correlation of the fog image and defogged image, which can represent the structural similarity. From the perspective of human visual perception, the normalized gray difference of defogged image is defined to describe the luminance of the image. Then, the fog image and defogged image are changed from RGB space to HSV space. Information entropy and histogram similarity of S component are used to assess the color performance of defogged image. Finally, with these three factors, a comprehensive image quality assessment model is established, which is used to make the objective evaluation and comparison. Experimental results demonstrate that the proposed method can achieve a consistent result with our subjective perception as well as obtain a good effectiveness and reliability.