Image Deblurring is a very popular area of research in all over the world. It is an illposed
problem which still does not have an ideal solution. Therefore, in order to analyse the …

Hyperspectral remote sensing images (HSIs) usually have high spectral resolution and low
spatial resolution. Conversely, multispectral images (MSIs) usually have low spectral and …

Blind image deblurring remains a topic of enduring interest. Learning based approaches,
especially those that employ neural networks have emerged to complement traditional …

In this paper we provide a review of the recent literature on Bayesian Blind Image
Deconvolution (BID) methods. We believe that two events have marked the recent history of …

Blind image deblurring, ie, deblurring without knowledge of the blur kernel, is a highly ill-
posed problem. The problem can be solved in two parts: 1) estimate a blur kernel from the …

As handheld video cameras are now commonplace and available in every smartphone
images and videos can be recorded almost everywhere at any time. However, taking a quick …

We propose a neural approach for fusing an arbitrary-length burst of photographs suffering
from severe camera shake and noise into a sharp and noise-free image. Our novel …

This paper presents a robust algorithm for estimating a single latent sharp image given
multiple blurry and/or noisy observations. The underlying multi-image blind deconvolution …

Video deblurring is a challenging problem as the blur is complex and usually caused by the
combination of camera shakes, object motions, and depth variations. Optical flow can be …

We developed a sparse multichannel blind deconvolution (SMBD) method. The method is a
modification of the multichannel blind deconvolution technique often called Euclid …