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

Image deblurring is a classical computer vision problem that aims to recover a sharp image
from a blurred image. To solve this problem, existing methods apply the Encode-Decode …

We tackle a fundamental problem to detect and estimate just noticeable blur (JNB) caused
by defocus that spans a small number of pixels in images. This type of blur is common …

Albeit great success has been achieved in image defocus blur detection, there are still
several unsolved challenges, eg, interference of background clutter, scale sensitivity and …

The detection of spatially-varying blur without having any information about the blur type is a
challenging task. In this paper, we propose a novel effective approach to address this blur …

Defocus blur detection aims to detect out-of-focus regions from an image. Although attracting
more and more attention due to its widespread applications, defocus blur detection still …

Defocus blur detection (DBD) is the separation of infocus and out-of-focus regions in an
image. This process has been paid considerable attention because of its remarkable …

Defocus blur detection (DBD) is aimed to estimate the probability of each pixel being in-
focus or out-of-focus. This process has been paid considerable attention due to its …

Due to the remarkable potential applications, defocus blur detection, which aims to separate
blurry regions from an image, has attracted much attention. Although significant progress …

Blur detection and segmentation for a single image without any prior information is a
challenging task. Numerous techniques for blur detection and segmentation have been …