This paper comprehensively reviews the recent development of image deblurring, including
non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques …

Taking another lesson from nature, the latest advances in image processing technology
seek to combine image data from several diverse types of sensors in order to obtain a more …

In this paper, we address the problem of no-reference quality assessment for digital pictures
corrupted with blur. We start with the generation of a large real image database containing …

Blind deconvolution, which comprises simultaneous blur and image estimations, is a
strongly ill-posed problem. It is by now well known that if multiple images of the same scene …

Blind image deconvolution is required in many applications of microscopy imaging, remote
sensing, and astronomical imaging. Unfortunately, in a single-channel framework, serious …

Existing multichannel blind restoration techniques assume perfect spatial alignment of
channels, correct estimation of blur size, and are prone to noise. We developed an …

Researchers have been working on the blind deconvolution problem from as early as 1975
and various methods have been developed over the period. Earlier methods were purely …

This paper presents an algorithm and its implementation for computing the approximate
GCD (greatest common divisor) of multivariate polynomials whose coefficients may be …

The issue of blur in images has kept researchers in the area of image processing busy for
over half a century, and the researchers at the Vision and Image Processing Laboratory, IIT …

This paper presents a regularization theory for numerical computation of polynomial greatest
common divisors and a convergence analysis, along with a detailed description of a …