孙怡

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:信息与通信工程学院

办公地点:海山楼A420

联系方式:lslwf@dlut.edu.cn

电子邮箱:lslwf@dlut.edu.cn

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Joint structural similarity and entropy estimation for coded-exposure image restoration

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论文类型:期刊论文

发表时间:2018-11-01

发表刊物:MULTIMEDIA TOOLS AND APPLICATIONS

收录刊物:SCIE

卷号:77

期号:22

页面范围:29811-29828

ISSN号:1380-7501

关键字:Coded-exposure; Smear length; Image restoration; Structural similarity; Entropy estimation

摘要:We address the image deblurring using coded exposure which can keep image content that may be lost by a traditional shutter. In the restoration of a coded exposure image, the automatic estimation of smear length is the key problem. Because the coded exposure image does not lose high frequency information of the image, the structural similarity compared with the original image is retained. In this paper, we propose a joint coarse to fine estimation method. By comparing structural similarity between the coded-exposure image and its restored image, the smear length can be roughly estimated first. And then the entropy of the restored image is further computed within a small range of the previously estimated smear length. An image that is restored with the wrong smear length will be far from the structure of the coded image that will have high entropy and low structure similarity with the coded exposure image.