Results 11 to 20 of about 4,369 (201)
MedDeblur: Medical Image Deblurring with Residual Dense Spatial-Asymmetric Attention
Medical image acquisition devices are susceptible to producing blurry images due to respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical image deblurring is still underexposed.
S. M. A. Sharif +5 more
doaj +1 more source
Burst Ranking for Blind Multi-Image Deblurring [PDF]
We propose a new incremental aggregation algorithm for multi-image deblurring with automatic image selection. The primary motivation is that current bursts deblurring methods do not handle well situations in which misalignment or out-of-context frames are present in the burst.
Fidel Alejandro Guerrero Peña +4 more
openaire +3 more sources
COMBINED PATCH-WISE MINIMAL-MAXIMAL PIXELS REGULARIZATION FOR DEBLURRING [PDF]
Deblurring is a vital image pre-processing procedure to improve the quality of images. It is a classical ill-posed problem. A new blind deblurring method based on image sparsity prior is proposed here.
J. Han, S. L. Zhang, Z. Ye
doaj +1 more source
An image defocus deblurring method based on gradient difference of boundary neighborhood
Background: For static scenes with multiple depth layers, the existing defocused image deblurring methods have the problems of edge ringing artifacts or insufficient deblurring degree due to inaccurate estimation of blur amount, In addition, the prior ...
Junjie TAO +6 more
doaj +1 more source
Blind Deblurring of Hyperspectral Document Images
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101026453. This work is published in the Lecture Notes in Computer Science book series (LNCS, volume 13373) as part of the Image Analysis and Processing, ICIAP 2022 ...
Marina Ljubenovic +3 more
openaire +2 more sources
Blind deblurring of foreground-background images [PDF]
This paper presents a method for deblurring an image consisting of two layers (a foreground layer and a background layer) which have suffered different, unknown blurs. This is a situation of practical interest. For example, it is common to find images in which we have a foreground object (e.g. a car) which has motion blur while the background is sharp (
Mariana S. C. Almeida, Luís B. Almeida
openaire +1 more source
Blind Text Image Deblurring Algorithm Based on Multi-Scale Fusion and Sparse Priors
The goal of blind text image deblurring is to obtain a clean text image from the given blurry text image without knowing the blur kernel. Sparsity-based methods have been shown their effectiveness in various blind text image deblurring models.
Zhe Li +3 more
doaj +1 more source
Reference-Based Multi-Level Features Fusion Deblurring Network for Optical Remote Sensing Images
Blind image deblurring is a long-standing challenge in remote sensing image restoration tasks. It aims to recover a latent sharp image from a blurry image while the blur kernel is unknown.
Zhiyuan Li +4 more
doaj +1 more source
Blind Image Deblurring: a Review
This is a review on blind image deblurring. First, we formulate the blind image deblurring problem and explain why it is challenging. Next, we bring some psychological and cognitive studies on the way our human vision system deblurs. Then, relying on several previous reviews, we discuss the topic of metrics and datasets, which is non-trivial to blind ...
openaire +2 more sources
Spectral Norm Regularization for Blind Image Deblurring [PDF]
Blind image deblurring is a well-known ill-posed inverse problem in the computer vision field. To make the problem well-posed, this paper puts forward a plain but effective regularization method, namely spectral norm regularization (SN), which can be regarded as the symmetrical form of the spectral norm.
Shuhan Sun +2 more
openaire +1 more source

