Results 51 to 60 of about 293,019 (211)
Quantitative comparisons among blind deblurring methods.
, 2018 Quantitative comparisons among blind deblurring methods.
Houjie Li (4918960) +4 more
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REGULARIZATION BY INEXACT KRYLOV METHODS WITH APPLICATIONS TO BLIND DEBLURRING [PDF]
, 2021 This paper is concerned with the regularization of large-scale discrete inverse problems by means of inexact Krylov methods. Specifically, we derive two new inexact Krylov methods that can be efficiently applied to unregularized or Tikhonov-regularized ...
Landman M. S., Gazzola S.
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Blind Image Deblurring via Local Maximum Difference Prior
IEEE Access, 2020 Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required.
Jing Liu +4 more
doaj +1 more source
Arbitrarily shaped Point Spread Function (PSF) estimation for single image blind deblurring [PDF]
, 2020 The research paper focuses on a challenging task faced in blind image deblurring (BID). It relates to the estimation of arbitrarily shaped (nonparametric or complex shaped) point spread functions (PSFs) of motion blur caused by camera handshake.
Khan, Aftab, Yin, Hujun; id_orcid
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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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International Endodontic Journal, EarlyView.ABSTRACT Background Computer vision methods based on artificial intelligence (AI) have found numerous applications in endodontic diagnosis and treatment planning. While most current applications employ discriminative deep learning models for detection and classification tasks, the field is now witnessing the rise of generative AI (GenAI), a class of AI
Hossein Mohammad‐Rahimi +6 more
wiley +1 more source
An Efficient Blind Image Deblurring Algorithm
, 2010 This paper presents a novel algorithm which concerns with the fast implement of blind image deblurring with a well-reconstructed original image. Firstly, we model both the original image and the blur utilizing the harmonic model in the Sobolev image ...
Su Xiao +3 more
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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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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
NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images [PDF]
, 2022 In recent years, deep neural network-based restoration methods have achieved state-of-the-art results in various image deblurring tasks. However, one major drawback of deep learning-based deblurring networks is that large amounts of blurry-clean image ...
Nair, Nithin Gopalakrishnan +2 more
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