Results 11 to 20 of about 13,900 (206)
MedDeblur: Medical Image Deblurring with Residual Dense Spatial-Asymmetric Attention
Mathematics, 2022 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
Iterative Dual CNNs for Image Deblurring
Mathematics, 2022 Image deblurring attracts research attention in the field of image processing and computer vision. Traditional deblurring methods based on statistical prior largely depend on the selected prior type, which limits their restoring ability.
Jinbin Wang, Ziqi Wang, Aiping Yang
doaj +1 more source
Reference-Based Multi-Level Features Fusion Deblurring Network for Optical Remote Sensing Images
Remote Sensing, 2022 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
Two-Level Wavelet-Based Convolutional Neural Network for Image Deblurring
IEEE Access, 2021 Image deblurring aims to restore the latent sharp image from the blurred one. In recent years, some learning-based image deblurring methods have achieved significant advances.
Yeyun Wu, Pan Qian, Xiaofeng Zhang
doaj +1 more source
IEEE Transactions on Multimedia, 2022 Deep learning-based blind image deblurring plays an essential role in solving image blur since all existing kernels are limited in modeling the real world blur. Thus far, researchers focus on powerful models to handle the deblurring problem and achieve decent results.
Chih-Hung Liang +3 more
openaire +2 more sources
A domain translation network with contrastive constraint for unpaired motion image deblurring
IET Image Processing, 2023 Most motion deblurring methods require a large amount of paired training data, which is nearly unreachable in practice. To overcome the limitation, a domain translation network with contrastive constraint for unpaired motion image deblurring is proposed.
Bingxin Zhao, Weihong Li
doaj +1 more source
Real Image Deblurring Based on Implicit Degradation Representations and Reblur Estimation
Applied Sciences, 2023 Most existing image deblurring methods are based on the estimation of blur kernels and end-to-end learning of the mapping relationship between blurred and sharp images.
Zihe Zhao +4 more
doaj +1 more source
Image Deblurring Based on Convex Non-Convex Sparse Regularization and Plug-and-Play Algorithm
Algorithms, 2023 Image deblurring based on sparse regularization has garnered significant attention, but there are still certain limitations that need to be addressed.
Yi Wang +4 more
doaj +1 more source
Guided Image Deblurring by Deep Multi-Modal Image Fusion
IEEE Access, 2022 Estimating sharp images from blurry observations is still a difficult task in the image processing research field. Previous works may produce deblurred images that lose details or contain artifacts.
Yuqi Liu, Zehua Sheng, Hui-Liang Shen
doaj +1 more source
Sensors, 2021 Complex marine environment has an adverse effect on the object detection algorithm based on the vision sensor for the smart ship sailing at sea. In order to eliminate the motion blur in the images during the navigation of the smart ship and ensure safety,
Hui Feng +3 more
doaj +1 more source