陈华松,宋旸,张正军,李振华.基于各向异性总变分的运动模糊盲复原方法[J].光电子激光,2015,26(6):1206~1214
基于各向异性总变分的运动模糊盲复原方法
Motion blind deblurring method by using anisotropic total variation
投稿时间:2014-11-27  
DOI:
中文关键词:  点扩散函数(PSF)估测  盲复原  各向异性总变分  运动模糊
英文关键词:point spread function (PSF) estimation  blind deblurring  anisotropic total variation  motion blurring
基金项目:国家自然科学基金(61371167)资助项目 (南京理工大学 信息物理与工程系 南京 210094)
作者单位
陈华松 南京理工大学 信息物理与工程系 南京 210094 
宋旸 南京理工大学 信息物理与工程系 南京 210094 
张正军 南京理工大学 信息物理与工程系 南京 210094 
李振华 南京理工大学 信息物理与工程系 南京 210094 
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中文摘要:
      针对目前运动模糊图像盲复原算法对图像边缘中 拐角结构复原不佳这一问题,提出了一种以各向异性总变分为图像和模糊核正则项的遥感图 像盲 复原方法。为便于进行数值计算,采用交叉算法和分裂布雷格曼迭代导出了本文提出的盲复 原方法的迭 代公式。实验结果表明,与基于同向异性总变分的盲复原方法以及基于小波框架的盲复原方 法相 比,本文方法不仅能估算出较精确的点扩散函数(PSF,point sp read function),有效地 去除图像的模糊效应,而且对图像边缘结构特别是拐角边缘结构的增强有着独特的优势。
英文摘要:
      The edge is an important feature of images,which is well used in many practical engineering fields,such as edge detection,object recognition and object tracking.However,the i mages often suffer from the blur effect due to motion between the object and the camera during the image acquisition pro cess.Numerous methods have been proposed for this problem,and the total variation based methods are the most po pular and efficient ones.But,images deblurred by using total variation based methods often suffer from serious st air-casing effects,which would damage the quality of the corners on the edge of images.In this paper,to protect the corn ers of the objects in images,an anisotropic total variation based regularization method is proposed for blind image deblurri ng,which regularizes both image and blur kernel by using anisotropic total variation instead of total variation.Bes ides,efficient iterative formula based on alternative method and split Bregman iteration is derived to apply the improved method in numerical experiments. Moreover,the results reveal that compared with the total variation based meth ods and framelet methods,the presented method can estimate the precise point spread function (PSF) an d remove the blurring as well as protecting the details of corners of objects.
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