中南大学学报（自然科学版）Issue(10)：3726-3732,7.DOI:10.11817/j.issn.1672-7207.2015.10.024
基于人眼视觉机理的雾霾图像质量提升算法
Lifting hazy image quality algorithm based on the human visual mechanism
摘要
Abstract
Since the results of mainstream defogging algorithms are far to reach human visual enjoyment and exhaust plenty of computing resource, a lifting color image quality algorithm based on the human visual mechanism was put forward in HSV color space through the Adams zone system and the non-subsampled contourlet transform under hazy weather. According to the algorithm, by imitating the process of papilla exposure, the maximum visual saliency was considered as medium grey standard to pull up dynamic ranges of the V component properly. Large amounts of detail features covered under fog and haze were given, the V component was then brought into non-subsampled contourlet filters to outstand image edge information according to the multi-frequency channel decomposition of human eyes. The H component remained unchanged because of the color constancy theory, but the S component merging together with the other adjusted-well components was revised by linear transform which relied on the prior statistics of color image components to keep them in good correlation. The simulation reveals that the novel algorithm not only improves visual effects of hazy images, but also provides higher practicability and less computing consumption.关键词
图像去雾/人眼视觉机理/亚当斯区域曝光理论/非下采样Contourlet变换/线性变换Key words
image defogging algorithm/human visual mechanism/adams zone system/non-subsampled contourlet transform/linear transform分类
信息技术与安全科学引用本文复制引用
周理,毕笃彦,何林远,柏航..基于人眼视觉机理的雾霾图像质量提升算法[J].中南大学学报（自然科学版）,2015,(10):3726-3732,7.基金项目
国家自然科学基金资助项目(61372167)(Project (61372167) supported by the National Natural Science Foundation of China) （61372167）
