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Mathematical Problems in Engineering
Volume 2017 (2017), Article ID 6089650, 14 pages
Research Article

A Single Image Deblurring Algorithm for Nonuniform Motion Blur Using Uniform Defocus Map Estimation

Department of Computer Science and Engineering, National Chung Hsing University, Taichung 402, Taiwan

Correspondence should be addressed to Jiunn-Lin Wu

Received 13 August 2016; Revised 23 December 2016; Accepted 15 January 2017; Published 13 February 2017

Academic Editor: Abdel-Ouahab Boudraa

Copyright © 2017 Chia-Feng Chang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


One of the most common artifacts in digital photography is motion blur. When capturing an image under dim light by using a handheld camera, the tendency of the photographer’s hand to shake causes the image to blur. In response to this problem, image deblurring has become an active topic in computational photography and image processing in recent years. From the view of signal processing, image deblurring can be reduced to a deconvolution problem if the kernel function of the motion blur is assumed to be shift invariant. However, the kernel function is not always shift invariant in real cases; for example, in-plane rotation of a camera or a moving object can blur different parts of an image according to different kernel functions. An image that is degraded by multiple blur kernels is called a nonuniform blur image. In this paper, we propose a novel single image deblurring algorithm for nonuniform motion blur images that is blurred by moving object. First, a proposed uniform defocus map method is presented for measurement of the amounts and directions of motion blur. These blurred regions are then used to estimate point spread functions simultaneously. Finally, a fast deconvolution algorithm is used to restore the nonuniform blur image. We expect that the proposed method can achieve satisfactory deblurring of a single nonuniform blur image.