多尺度细节融合的多曝光高动态图像重建  

Multi-exposure HDR images reconstruction based on multi-scale detail fusion

作　　者：付争方[1] 朱虹[2] FU Zhengfang;ZHU Hong(Department of Electronics and Information Engineering,Ankang University,Ankang,Shaanxi 725000,China;School of Automation and Information Engineering,Xi＇an University of Technology,Xi＇an 710048,China)

机构地区：[1]安康学院电子与信息工程系,陕西安康725000 [2]西安理工大学自动化与信息工程学院,西安710048

出　　处：《计算机工程与应用》2018年第24期182-187,197,共7页Computer Engineering and Applications

基　　金：安康学院高层次人才专项项目(No.2016AYQDZR06)

摘　　要：同一场景不同曝光的图像序列,常出现曝光不足或曝光过度的区域,造成高亮或阴暗处的细节损失。针对这一问题,提出的多尺度细节融合的多曝光高动态图像重建方法,根据图像的对比度、饱和度、适度曝光量等三个测度因子生成原始多曝光图像的权重图,对分解的权重高斯金字塔进行Dirichlet函数映射,保证信息丰富区域权值最大,通过拉普拉斯金字塔重建,使得融合图像所包含的细节信息最大化并且最大限度地减少失真。Image sequences are exposed differently in the same scene, often in areas that are underexposed or overexposed, thereby causing loss to the highlight details or the shadows. In order to solve this problem, multi-exposure HDR images reconstruction based on multi-scale detail fusion is proposed, which considers three measure factor of image, such as contrast, saturation and well-exposedness. This thesis maps the decomposed weight Gaussian pyramid through Dirichlet function, and assigns maximum weights for areas with rich information, then the HDR image can be reconstructed by the Laplace pyramid, which contains the maximal detail information and minimal distortion.

关 键 词：高动态范围图像 多曝光图像 图像融合 多尺度细节 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]