Results 21 to 30 of about 293,019 (211)

Blind motion deblurring using improved DeblurGAN

IET Image Processing
To develop a fast and effective image deblurring method, the blind recovery of motion‐blurred images based on DeblurGAN(GAN, Generative Adversarial Networks) is researched.Firstly, the number of residual modules in the DeblurGAN network is changed, and ...
Wentao Ji, Xing Chen, Yihong Li
doaj   +2 more sources

A Fast Nonlinear Sparse Model for Blind Image Deblurring. [PDF]

J Imaging
Blind image deblurring, which requires simultaneous estimation of the latent image and blur kernel, constitutes a classic ill-posed problem. To address this, priors based on L2, L1, and Lp regularizations have been widely adopted.
Zhang Z, Guo Z, Xu Z, Chen H, Wang C, Song Y, Lai J, Ji Y, Li Z.   +8 more
europepmc   +2 more sources

Learning Blind Motion Deblurring [PDF]

2017 IEEE International Conference on Computer Vision (ICCV), 2017
As handheld video cameras are now commonplace and available in every smartphone, images and videos can be recorded almost everywhere at anytime. However, taking a quick shot frequently yields a blurry result due to unwanted camera shake during recording or moving objects in the scene.
Wieschollek, P., Hirsch, M., Schoelkopf, B., Lensch, H.   +3 more
openaire   +4 more sources

Blind deblurring of natural images [PDF]

2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008
A new method to perform blind image deblurring is proposed. Very few assumptions are made on the blurring filter and on the original image: the blurring filter is assumed to have limited support and the original image is assumed to be a sharp natural image. A new prior is used, which gives higher probability to images with sharp edges.
Mariana S. C. Almeida, Luís B. Almeida
openaire   +1 more source

Discriminative Non-blind Deblurring [PDF]

2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013
Non-blind deblurring is an integral component of blind approaches for removing image blur due to camera shake. Even though learning-based deblurring methods exist, they have been limited to the generative case and are computationally expensive. To this date, manually-defined models are thus most widely used, though limiting the attained restoration ...
Uwe Schmidt, Carsten Rother, Sebastian Nowozin, Jeremy Jancsary, Stefan Roth   +4 more
openaire   +1 more source

A Single Image Deblurring Approach Based on a Fractional Order Dark Channel Prior

International Journal of Applied Mathematics and Computer Science, 2022
The dark channel prior has been successfully applied to solve the blind deblurring problem on different scene images. Since the dark channel of the blurry-noise image is similar to that of the corresponding clear image, the sparsity of the dark channel ...
Yu Xiaoyuan, Xie Wei, Yu Jinwei
doaj   +1 more source

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, Rizwan Ali Naqvi, Zahid Mehmood, Jamil Hussain, Ahsan Ali, Seung-Won Lee   +5 more
doaj   +1 more source

An image defocus deblurring method based on gradient difference of boundary neighborhood

Virtual Reality & Intelligent Hardware, 2023
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, Yinghui WANG, Haomiao M.A, Tao YAN, Lingyu AI, Shaojie ZHANG, Wei LI   +6 more
doaj   +1 more source

Image Deblurring Based on Residual Attention and Multi-feature Fusion [PDF]

Jisuanji kexue, 2023
Non-uniform blind deblurring in dynamic scenes is a challenging computer vision problem.Although deblurring algorithms based on deep learning have made great progress,there are still problems such as incomplete deblurring and loss of details.To solve ...
ZHAO Qian, ZHOU Dongming, YANG Hao, WANG Changchen
doaj   +1 more source

COMBINED PATCH-WISE MINIMAL-MAXIMAL PIXELS REGULARIZATION FOR DEBLURRING [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020
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