Title :
An Optimal Blind Temporal Motion Blur Deconvolution Filter
Author :
Tendero, Y. ; Morel, Jean-Michel
Author_Institution :
Dept. of Math., Univ. of California, Los Angeles, Los Angeles, CA, USA
Abstract :
The frames of a video sequence can be improved by a spatial deconvolution of any motion blur not exceeding two pixels per frame. Yet, this requires an accurate blur estimation and local deconvolution, which is problematic for multiple local motions. We introduce an optimal temporal blur deconvolution filter restoring blindly any nonuniform motion blur with an amplitude below one pixel per frame. The discrete filter has a very low complexity of about 20 operations per pixel. Experiments illustrate the method on simulated data, real movies and on sequences from the Middlebury database.
Keywords :
deconvolution; filtering theory; image motion analysis; image restoration; image sequences; video signal processing; Middlebury database; any motion blur; blur estimation; discrete filter; local deconvolution; multiple local motions; nonuniform motion blur; optimal blind temporal motion blur deconvolution filter; optimal temporal blur deconvolution filter; real movies; simulated data; spatial deconvolution; video sequence; Cameras; Deconvolution; Estimation; Fourier transforms; Kernel; Motion pictures; Noise; Blind deconvolution; motion blur; optimal filter;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2013.2254115