Stripe and random noise are two different degradation phenomena that commonly coexist in
optical remote sensing images, and they are often modeled as inverse problems. In model …

In agriculture, fruit picking robots on the ground have difficulty adapting to the terrain
conditions of mountain orchards and cannot pick longan fruit from tall longan trees. In this …

Due to the ill-posed nature of image restoration, seeking a meaningful image prior is still a
great challenge in the field of image processing. The total variation with overlapping group …

Image deblurring and super-resolution (SR) are computer vision tasks aiming to restore
image detail and spatial scale, respectively. Despite significant research effort over the past …

Non-uniform motion blur caused by camera shake or object motion is a common artifact in
videos captured by hand-held devices. Recent advances in video deblurring have shown …

This paper denotes to obtain an accuracy blur kernel and a shape image. An efficient
method that blind deconvolution for image deblurring based on edge enhancement and …

The major task of traditional motion deblurring methods is to estimate the blur kernel and
restore the latent image. In low-light conditions, the pointolite is likely to produce saturated …

In this paper, we address the challenge of image deblurring in the presence of Gaussian
noise. To achieve high-quality image restoration, we introduce an optimization framework …

Blind image deconvolution is a typically ill-conditioned inverse problem that requires
additional information to constrain the solution space. The purpose of this paper is to …