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The Scientific World Journal
Volume 2014 (2014), Article ID 649272, 7 pages
Research Article

Fast Motion Deblurring Using Sensor-Aided Motion Trajectory Estimation

Department of Image, Chung-Ang University, Seoul 156-756, Republic of Korea

Received 29 July 2014; Accepted 10 October 2014; Published 4 November 2014

Academic Editor: Yung-Kuan Chan

Copyright © 2014 Eunsung Lee 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.


This paper presents an image deblurring algorithm to remove motion blur using analysis of motion trajectories and local statistics based on inertial sensors. The proposed method estimates a point-spread-function (PSF) of motion blur by accumulating reweighted projections of the trajectory. A motion blurred image is then adaptively restored using the estimated PSF and spatially varying activity map to reduce both restoration artifacts and noise amplification. Experimental results demonstrate that the proposed method outperforms existing PSF estimation-based motion deconvolution methods in the sense of both objective and subjective performance measures. The proposed algorithm can be employed in various imaging devices because of its efficient implementation without an iterative computational structure.