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Proceedings Paper

Removing shift-variant motion blur from an image using Poisson interpolation
Author(s): Chunjian Ren; Xiaoqiang Liu; Yi Qiao
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Paper Abstract

Photographs captured with sufficient exposure under low-light conditions are usually blurred if there are moving objects. Under some circumstances, the restoration is challenging because of complicated motion blur such as rotation and distortion. In this paper, we propose a novel method to replace the motion blur objects of blurred image with the corresponding sharp objects of flash image using Poisson interpolation. First, assisted by the sufficient exposure blurred image, we adopt graph-cut to minimize a simple cost function and extract the intensely lightened sharp objects in the flash image. Second, we interpolate the extracted sharp objects into the blurred image, and then remove the remnant blur around the sharp objects through gradient domain Poisson interpolation. Further, a simple method is designed that the user can interactively adjust the brightness and contrast of flash area in the synthetical image. The experiments demonstrate that our algorithms are efficient.

Paper Details

Date Published: 30 October 2009
PDF: 7 pages
Proc. SPIE 7495, MIPPR 2009: Automatic Target Recognition and Image Analysis, 749502 (30 October 2009); doi: 10.1117/12.833237
Show Author Affiliations
Chunjian Ren, Donghua Univ. (China)
Shanghai Key Lab. of Computer Software Evaluating and Testing (China)
Xiaoqiang Liu, Donghua Univ. (China)
Yi Qiao, Donghua Univ. (China)


Published in SPIE Proceedings Vol. 7495:
MIPPR 2009: Automatic Target Recognition and Image Analysis
Tianxu Zhang; Bruce Hirsch; Zhiguo Cao; Hanqing Lu, Editor(s)

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