Universal deblurring method for real images using transition region

Hanyu Hong; Liangcheng Li; In Kyu ParkTianxu Zhang

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Universal deblurring method for real images using transition region

机译：Universal deblurring method for real images using transition region

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摘要

In this paper, we present a universal deblurring method for real images without prior knowledge of the blur source. The proposed method uses the transition region of the blurred image to estimate the point spread function (PSF). It determines the main edges of the blurred image with high edge measures based on the difference of Gaussians (DoG) operator. Those edge measures are used to predict the transition region of the sharp image. By using the transition region, we select the pixels of the blurred image to form a series of equations for calculating the PSF. In order to overcome noise disturbance, the optimal method based on the anisotropic adaptive regularization is used to estimate the PSF, in which the constraints of non-negative and spatial correlations are incorporated. Once the PSF is estimated, the blurred image is effectively recovered by employing nonblind restoration. Experimental results show that the proposed method performs effectively for real images with different blur sources.

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来源
《Optical Engineering》 |2012年第4期|047006-1-047006-10|共10页
作者
Hanyu Hong; Liangcheng Li; In Kyu ParkTianxu Zhang;
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作者单位

Wuhan Institute of Technology, Laboratory for Image Processing and Intelligent Control, Wuhan, 430074, China;

Inha University, School of Information and Communication Engineering, Incheon 402-751, Korea;

Huazhong University of Science and Technology, Institute for Pattern Recognition and Al, Wuhan, 430074, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
image deblurring; transition region; point spread function;

Universal deblurring method for real images using transition region

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