Results 11 to 20 of about 441,411 (171)
A Fast Nonlinear Sparse Model for Blind Image Deblurring [PDF]
J ImagingBlind 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.
Yang Song +8 more
core +2 more sources
Multi-scale progressive blind face deblurring
Complex & Intelligent Systems, 2022 Blind face deblurring aims to recover a sharper face from its unknown degraded version (i.e., different motion blur, noise). However, most previous works typically rely on degradation facial priors extracted from low-quality inputs, which generally leads
Hao Zhang +7 more
doaj +2 more sources
Localized Quadratic RF Encoded Spin‐Echo With Spiral‐PRIME Reconstruction: A Practical Alternative to 3D FSE for High‐Resolution Volumetric Brain MRI [PDF]
Magnetic Resonance in Medicine, Volume 96, Issue 6, Page 2615-2628, December 2026.ABSTRACT Purpose To extend localized quadratic (LQ) RF encoded spin‐echo imaging with acquisition and reconstruction strategies that improve efficiency and artifact robustness, positioning it as a practical alternative to 3D FSE for high‐resolution volumetric brain MRI.
Guruprasad Krishnamoorthy +2 more
wiley +2 more sources
Blind Image Deblurring Based on Local Edges Selection
Applied Sciences, 2019 The edges of images are less sparse when images become blurred. Selecting effective image edges is a vital step in image deblurring, which can help us to build image deblurring models more accurately.
Yue Han, Jiangming Kan
doaj +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingBlind deblurring of optical remote sensing images has been a longstanding challenge. In recent years, many learning-based deblurring algorithms have been greatly developed.
Zhiyuan Li +4 more
doaj +2 more sources
Multi‐Scale Frequency Enhancement Network for Blind Image Deblurring
IET Image Processing, Volume 19, Issue 1, January/December 2025.We propose a multi‐scale frequency enhancement network (MFENet) for blind image deblurring, which integrates multi‐scale feature extraction and frequency enhancement to recover fine details. MFENet includes a multi‐scale feature extraction module (MS‐FE) and a frequency enhanced blur perception module (FEBP) to improve performance on deblurring ...
YaWen Xiang +5 more
wiley +2 more sources
Application of Blind Deblurring Reconstruction Technique to SPECT Imaging [PDF]
International Journal of Biomedical Imaging, 2007 An SPECT image can be approximated as the convolution of the ground truth spatial radioactivity with the system point spread function (PSF). The PSF of an SPECT system is determined by the combined effect of several factors, including the gamma camera ...
Heng Li, Yibin Zheng
doaj +2 more sources
Tikrit Journal of Engineering Sciences, 2014 In image deblurring, we try to recover the original, sharp image by using a mathematical model of the blurring process. There are several techniques to recover the original image, but they could not recover the image exactly.
Shayma Wail Nourildean Mohammed Ismaeel Khalil
doaj +1 more source
Noise-blind image deblurring [PDF]
, 2017 We present a novel approach to noise-blind deblurring, the problem of deblurring an image with known blur, but unknown noise level. We introduce an efficient and robust solution based on a Bayesian framework using a smooth generalization of the 0-1 loss.
Roth, Stefan +5 more
core +3 more sources
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