基于HSI颜色空间和暗原色先验的去雾算法  

Haze Removal Algorithm Based on HSI Color Space and Dark Channel Prior

作　　者：宋瑞霞[1] 孙相东 王小春[2] SONG Ruixia;SUN Xiangdong;WANG Xiaochun(College of Sciences, North China University of Technology, Beijing 100144;College of Sciences, Beijing Forestry University, Beijing 100083)

机构地区：[1]北方工业大学理学院,北京100144 [2]北京林业大学理学院,北京100083

出　　处：《系统科学与数学》2017年第10期2111-2120,共10页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(61571046;61272026);国家重点研发计划(2017YFF0209806)资助课题

摘　　要：为了消除雾天对图像采集的影响,提高图像的质量,解决传统去雾技术对图像信息保留不完整,清晰度不好的问题,文章提出一种转换颜色空间的暗原色先验去雾改进算法.首先将图像的RGB颜色空间转换到HSI颜色空间,然后保持色调分量H不变;对亮度分量I进行暗原色先验去雾,并在进行暗原色去雾时,采用更为精确的四叉树算法求取大气光值;对饱和度分量S进行V变换,低频重构出新的饱和度分量,降低纹理、噪声等信息的影响并提高饱和度.对于含有大片天空区域的图像,则通过进一步提高最小透射率,可以有效地去除图像中的雾和霾,同时还避免了图像出现颜色失真的状况.实验结果证明,与经典的去雾算法相比较,文章算法去雾效果明显,图像清晰度高,图像信息保留比较完整,色彩更加真实自然,且时间复杂度较低.To eliminate the influence of foggy weather on image acquisition, improve image quality and solve the problem of incomplete retention of image information and poor articulation for traditional dehazing techniques, this paper proposes an improved dark channel prior based image dehazing algorithm using color space conversion. The RGB color space of the image is first converted to the HSI color space, while the hue component H remains unchanged. Then we perform dark channel prior based image dehazing on the intensity component I, and simultaneously calculate the atmospheric light value using the more accurate quad-tree algorithm. The saturation component S is performed by V-transform, and the low-frequency saturation is reconstructed to reduce the influence of texture and noise, and to increase saturation. For images containing large areas of the sky, fog and haze can be effectively removed by further improving the minimum transmittance, and color distortion can be also avoided in this process. Experiment results show that the algorithm has obvious haze removal effect, the dehazed image has higher clarity and more realistic color, retains relatively complete image information, and has lower time complexity compared with the classic haze removal algorithm.

关 键 词：暗原色先验 图像去雾 HSI颜色空间 四叉树 V-变换 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]