基于开运算暗通道和优化边界约束的图像去雾算法  

Image Defogging Algorithm Based on Opening Dark Channel and Improved Boundary Constraint

作　　者：杨红 崔艳[1] YANG Hong;CUI Yan(School of Science, Tianj in Polytechnic University, Tianj in 300387, Chin)

机构地区：[1]天津工业大学理学院,天津300387

出　　处：《光子学报》2018年第6期238-244,共7页Acta Photonica Sinica

基　　金：天津市应用基础及前沿技术研究计划重点项目(No.12JCZDJC27800)资助~~

摘　　要：将有雾图像分割为非天空区域和天空区域,对于非天空区域,提出一种优化的暗原色先验思想,即开运算暗通道算法;对于天空区域,引入具有保边去噪的双边滤波算法,提出一种改进的边界约束算法.运用两种算法分别估计两个区域的透射率,然后利用大气物理散射模型复原各区域,最后合并两个无雾区域得到去雾图像.实验结果表明,该算法很大程度提高了有雾图像尤其是含天空的有雾图像的图像对比度,改善了颜色失真问题.The fog image is divided into non-sky area and sky area. For the non-sky area,a method of optimization of dark channel prior thought,namely the opening dark channel algorithm,is presented. For the sky area,an improved boundary constraint algorithm is put forward by introducing bilateral filter algorithm which has the role of edge-preserving and denoising. The two different algorithms are utilized to estimate the more accurate transmission map in their own areas respectively. Afterwards,the two defog area can be obtained by exploiting the atmospheric physical scattering model. Finally,the haze image is restored by combining the two defog areas. The experimental results show that the proposed algorithm has greatly improve the image contrast and ameliorate the color distortion problem in haze images,especially for haze images which contain the sky area.

关 键 词：图像增强 图像去雾 天空分割 暗通道先验 边界约束 双边滤波 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]