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

Numerous single-image super-resolution algorithms have been proposed in the literature,
but few studies address the problem of performance evaluation based on visual perception …

The recent advances in hardware and imaging systems made the digital cameras
ubiquitous. Although the development of hardware has steadily improved the quality of …

In many sparse coding based image restoration and image classification problems, using
non-convex p-norm minimization (0 top po1) can often obtain better results than the convex …

Images taken in low-light conditions with handheld cameras are often blurry due to the
required long exposure time. Although significant progress has been made recently on …

It is often desirable to evaluate an image based on its quality. For many computer vision
applications, a perceptually meaningful measure is the most relevant for evaluation; …

Modern imaging optics are highly complex systems consisting of up to two dozen individual
optical elements. This complexity is required in order to compensate for the geometric and …

Most existing image fusion methods assume that at least one input image contains high-
quality information at any place of an observed scene. Thus, these fusion methods will fail if …

Block transform coded images usually suffer from annoying artifacts at low bit rates, caused
by the coarse quantization of transform coefficients. In this paper, we propose a new method …

The restoration of a blurry or noisy image is commonly performed with a MAP estimator,
which maximizes a posterior probability to reconstruct a clean image from a degraded …