Quality measures for blind image deblurring

Abstract

Blind image deblurring is limited by the unavailability or in many cases little information about the PSF. If the PSF is estimated, then deblurring simplifies to just deconvolving the blurred image with the PSF using any conventional deblurring filter. We have recently proposed a blind deblurring scheme using kurtosis measures. The scheme is able to deblur degraded images of unknown types such as out-of-focus, motion or atmospheric turbulence. However, for blurred images whose original are unknown, it is impossible to measure the improvement, unlike in simulated blurring cases. In this paper, a way of measuring the quality improvement of the deblurring is suggested. The deblurred image is-reblurred by the estimated PSF and then the PSNR between the original blurred image and the re-blurred image is calculated as an indication of deblurring quality. Deblurring filters often produce noise and ringing artifacts in the deblurred image, which will be less severe when a candidate filter similar to the true PSF is used. This quality measures further enhance the blind deblurring scheme and has been tested on both synthetic and real blurred images.