Camera shake or target movement often leads to undesired blur effects in videos captured
by a hand-held camera. Despite significant efforts having been devoted to video-deblur …

Images taken under the low-light condition often contain blur and saturated pixels at the
same time. Deblurring images with saturated pixels is quite challenging. Because of the …

As an integral component of blind image deblurring, non-blind deconvolution removes
image blur with a given blur kernel, which is essential but difficult due to the ill-posed nature …

Blind deblurring has attracted much interest with its wide applications in reality. The blind
deblurring problem is usually solved by estimating the intermediate kernel and the …

The goal of dynamic scene deblurring is to remove the motion blur presented in a given
image. To recover the details from the severe blurs, conventional convolutional neural …

Blind image deblurring (BID) has been extensively studied in computer vision and adjacent
fields. Modern methods for BID can be grouped into two categories: single-instance methods …

Video deblurring is to restore sharp frames from a blurry sequence. It is a challenging low-
level vision task because the blur caused by camera shake, object motions and depth …

In this study, we propose a patch-wise maximum gradient (PMG) prior for effective blind
image deblurring. Our work is motivated by the fact that the maximum gradient values of non …

Blind image deblurring is a challenging problem due to its ill-posed nature, of which the
success is closely related to a proper image prior. Although a large number of sparsity …

The irradiance range of the real-world scene is often beyond the capability of digital
cameras. Therefore, High Dynamic Range (HDR) images can be generated by fusing …