Blind image deconvolution: Motion blur estimation

Abstract

This report discusses methods for estimating linear motion blur. The blurred image is modeled as a convolution between the original image and an unknown point-spread function. The angle of motion blur is estimated using three different approaches. The first employs the cepstrum, the second a Gaussian filter, and the third the Radon transform. To estimate the extent of the motion blur, two different cepstral methods are employed. The accuracy of these methods is evaluated using artificially blurred images with varying degrees of noise added. Finally, the best angle and length estimates are combined with existing deconvolution methods to see how well the image is deblurred.