Phase unwrapping (PU) is a technique to reconstruct original phase images from their noisy
wrapped counterparts finding many applications in scientific imaging. Although supervised …

Blur artifacts can seriously degrade the visual quality of images, and numerous deblurring
methods have been proposed for specific scenarios. However, in most real-world images …

Motion deblurring is one of the fundamental problems of computer vision and has received
continuous attention. The variability in blur, both within and across images, imposes …

Blind image deconvolution (BID) is a classic yet challenging problem in the field of image
processing. Recent advances in deep image prior (DIP) have motivated a series of DIP …

Natural images captured by mobile devices often suffer from multiple types of degradation,
such as noise, blur, and low light. Traditional image restoration methods require manual …

This paper focuses on the dataset-free Blind Image Super-Resolution (BISR). Unlike existing
dataset-free BISR methods that focus on obtaining a degradation kernel for the entire image …

Blind image deblurring problem needs to estimate both the latent image and the blur kernel,
which is an active and challenging task in image processing and computer vision. To tackle …

Blind image deblurring is a fundamental and important task in the field of computer vision.
With the continuous progress of technology, blind image deblurring methods have achieved …

This article proposes a novel “Deep Salient Image Deblurring (DSID) Framework” for kernel-
free image deblurring that combines saliency detection and variational autoencoders and …

Logo detection is a challenging task in computer vision, especially when the logos are
blurred or distorted in the images. Image deblurring is a technique that can improve the …