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 …

In this paper, we propose a new theory of invariants to Gaussian blur. We introduce a notion
of a primordial image as a canonical form of all Gaussian blur-equivalent images. The …

In this paper, we propose a single image deblurring algorithm to remove spatially variant
defocus blur based on the estimated blur map. Firstly, we estimate the blur map from a …

Convolutional neural networks (CNN) have shown its excellent performance in computer
vision fields. Recently, they are successfully applied to image restoration. This paper …

Defocus map estimation (DME) is highly important in many computer vision applications.
Nearly, all existing approaches for DME from a single image are based on a one-parameter …

Blind image deblurring has been a challenging issue due to the unknown blur and
computation problem. Recently, the matrix-variable optimization method successfully …

The paper presents a new theory of invariants to Gaussian blur. Unlike earlier methods, the
blur kernel may be arbitrary oriented, scaled and elongated. Such blurring is a semi-group …

Super resolution image reconstruction under unknown Gaussian blur has been a
challenging topic. Advanced optimization-based works for blind image super-resolution (SR) …

In this study, reducing motion blur in images taken by our unmanned aerial vehicle is
investigated. Since shakes of unmanned aerial vehicle cause motion blur in taken images …

Blur in facial images significantly impedes the efficiency of recognition approaches.
However, most existing blind deconvolution methods cannot generate satisfactory results …