title: Fast motion deblurring using sensor-aided motion trajectory estimation.
abstract: 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.
authors.affiliation: Department of Image, Chung-Ang University, Seoul 156-756, Republic of Korea.
authors.forename: Eunsung
authors.initials: E
authors.lastname: Lee
authors.affiliation: Department of Image, Chung-Ang University, Seoul 156-756, Republic of Korea.
authors.forename: Eunjung
authors.initials: E
authors.lastname: Chae
authors.affiliation: Department of Image, Chung-Ang University, Seoul 156-756, Republic of Korea.
authors.forename: Hejin
authors.initials: H
authors.lastname: Cheong
authors.affiliation: Department of Image, Chung-Ang University, Seoul 156-756, Republic of Korea.
authors.forename: Joonki
authors.identifier: 0000-0002-8593-7155
authors.initials: J
authors.lastname: Paik
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical; D009038:Motion; D012984:Software