Inverse imaging problems are inherently underdetermined, and hence, it is important to
employ appropriate image priors for regularization. One recent popular prior-the graph …

In this paper, we provide a short review of Retinex and then present a unifying framework.
The fundamental assumption of all Retinex models is that the observed image is a …

We introduce a generic convex energy functional that is suitable for both grayscale and
vector-valued images. Our functional is based on the eigenvalues of the structure tensor …

The choice of a proper regularization measure plays an important role in the field of image
processing. One classical approach treats color images as two-dimensional surfaces …

Models related to the Euler's elastica energy have proven to be useful for many applications
including image processing. Extending elastica models to color images and multichannel …

The introduction of consumer RGB-D scanners set off a major boost in 3D computer vision
research. Yet, the precision of existing depth scanners is not accurate enough to recover fine …

The ubiquity of the Laplace-Beltrami operator in shape analysis can be seen by observing
the wide variety of applications where it has been found to be useful. Here we demonstrate a …

Mappings between color spaces are ubiquitous in image processing problems such as
gamut mapping, decolorization, and image optimization for color‐blind people. Simple color …

Advanced networks excel in Blind Image Quality Assessment (BIQA), however accurate
estimation of quality scores remains challenging due to unrevealed features extricated …

Patch-based techniques are proven to generate promising results and outperform many of
the existing state-of-art techniques for most of the applications in digital image processing. In …