An Optimal Blind Temporal Motion Blur Deconvolution Filter

Yohann Tendero, Jean-Michel Morel

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.