基于块匹配的低光度图像对融合方法  

Low-light Image Pairs Fusion Method Based on Patch-match

作　　者：王光霞 冯华君[1] 徐之海[1] 李奇[1] 陈跃庭[1] WANG Guang-xia;FENG Hua-jun;XU Zhi-hai;LI Qi;CHEN Yue-ting(State Key Laboratory of Modern Optical Instrumentation,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]浙江大学现代光学仪器国家重点实验室,杭州310027

出　　处：《光子学报》2019年第4期204-213,共10页Acta Photonica Sinica

基　　金：浙江省科学技术项目(No.2017C01033);国家自然科学基金(No.61475135)~~

摘　　要：针对低光度条件下长曝光图像与短曝光图像的融合问题,提出了一种基于块匹配的图像融合方法,将低光度图像对融合成为一张更好的图像.首先提出基于金字塔多尺度模型的双向鬼影检测算法,该算法降低了噪声和欠曝对鬼影检测的影响,用于准确检测低光度场景中图像对之间由于物体运动造成的不一致区域;随后利用块匹配算法重建鬼影区域;最后运用改善边缘特性的泊松融合算法提取两次曝光图像中的信息生成结果图像.实验结果表明,该方法有效地保留了短曝光图像的边缘锐度,并保持了长曝光图像的色彩、亮度和细节.Aiming at the fusion problem of long-exposure image and short-exposure image under low-light condition,a patchmatch-based method is proposed to fuse low-light image pair into a better one.Firstly,a bi-directional ghost detection scheme based on pyramid multi-scale algorithm is proposed,which reduces the influence of noise and under-exposure on ghost detection,and is used to accurately detect the inconsistent region caused by the motion of the object between the image pairs.Then,the patchmatch algorithm is used to reconstruct the ghost region.And finally the Poisson fusion algorithm of improved edge characteristics is used to extract the information from the two exposures.Experimental results show that the proposed method effectively preserves sharp outlines of the short-exposed image,and maintains the color,brightness and details of the long-exposed image.

关 键 词：图像处理 图像融合 块匹配 泊松方程 去鬼影 图像增强 图像去噪 

分 类 号：TN911.73[电子电信—通信与信息系统]