Results 41 to 50 of about 4,539 (201)
Blind and Non-Blind Deconvolution-Based Image Deblurring Techniques for Blurred and Noisy Image
Tikrit Journal of Engineering Sciences: Image deblurring is a common issue in low-level computer vision aiming to restore a clear image from a blurred input image. Deep learning innovations have significantly advanced the solution to this issue, and numerous deblurring networks have been ...
Shayma Wail Nourildean
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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
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A Two-Stage Network for Image Deblurring
IEEE Access, 2021 Blind deblurring is a typical challenge in image processing, carried out to correct various complex types of distortions that occur in the real world. Although learning-based deblurring methods have substantially outperformed the traditional algorithms ...
Ze Pan, Qunbo Lv, Zheng Tan
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Phase and TV Based Convex Sets for Blind Deconvolution of Microscopic Images [PDF]
, 2015 In this article, two closed and convex sets for blind deconvolution problem are proposed. Most blurring functions in microscopy are symmetric with respect to the origin.
Cetin, A. Enis +2 more
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Adaptive blind image deblurring and denoising
Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 413-441, March 2026.Abstract Blind image deblurring aims to reconstruct the original image from its blurred version without knowing the blurring mechanism. This is a challenging ill‐posed problem because there are infinitely many possible solutions. The ill‐posedness is further exacerbated if the blurring mechanism depends on the pixel location.
Yicheng Kang +2 more
wiley +1 more source
A Motion Deblur Method Based on Multi-Scale High Frequency Residual Image Learning
IEEE Access, 2020 Non-uniform blind deblurring of dynamic scenes has always been a challenging problem in image processing because of the diverse of blurring sources. Traditional methods based on energy minimization cannot make accurate kernel estimation. It leads to that
Keng-Hao Liu +3 more
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Recent Progress in Image Deblurring [PDF]
, 2014 This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques.
Tao, Dacheng, Wang, Ruxin
core
Blind Image Deblurring: a Review
, 2022 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
Blind Image Deblurring In The Edge Domain [PDF]
, 2004 Publication in the conference proceedings of EUSIPCO, Viena, Austria ...
COLONNESE, Stefania +3 more
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Multi‐Scale Transformer for Image Restoration
CAAI Transactions on Intelligence Technology, Volume 11, Issue 1, Page 41-54, February 2026.ABSTRACT Although Transformer‐based image restoration methods have demonstrated impressive performance, existing Transformers still insufficiently exploit multiscale information. Previous non‐Transformer‐based studies have shown that incorporating multiscale features is crucial for improving restoration results.
Wuzhen Shi +6 more
wiley +1 more source