Results 21 to 30 of about 2,318 (187)
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
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Motion deblurring as optimisation [PDF]
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing, 2010 Motion blur is one of the most common causes of image degradation. It is of increasing interest due to the deep penetration of digital cameras into consumer applications. In this paper, we start with a hypothesis that there is sufficient information within a blurred image and approach the deblurring problem as an optimisation process where the ...
V. S. Rao Veeravasarapu +1 more
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IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016 We describe a learning-based approach to blind image deconvolution. It uses a deep layered architecture, parts of which are borrowed from recent work on neural network learning, and parts of which incorporate computations that are specific to image deconvolution.
Schuler, C. +3 more
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Meta Transferring for Deblurring
CoRR, 2022 Accepted at BMVC ...
Po-Sheng Liu +5 more
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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
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IEEE Access, 2020 We propose an $L_{p}$ -norm-based sparse regularization model for license plate deblurring, which is motivated by distinctive properties of license plate images. For the blurred images, general deblurring methods may restore a good overall visual effect.
Chenping Zhao +4 more
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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
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Blur2Sharp: A GAN-Based Model for Document Image Deblurring
International Journal of Computational Intelligence Systems, 2021 The advances in mobile technology and portable cameras have facilitated enormously the acquisition of text images. However, the blur caused by camera shake or out-of-focus problems may affect the quality of acquired images and their use as input for ...
Hala Neji +4 more
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Graph Laplacian for image deblurring [PDF]
ETNA - Electronic Transactions on Numerical Analysis, 2021 Image deblurring is relevant in many fields of science and engineering. To solve this problem, many different approaches have been proposed and among the various methods, variational ones are extremely popular. These approaches are characterized by substituting the original problem with a minimization one where the functional is composed of two terms ...
Bianchi D. +3 more
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Wasserstein Generative Adversarial Network Based De-Blurring Using Perceptual Similarity
Applied Sciences, 2019 The de-blurring of blurred images is one of the most important image processing methods and it can be used for the preprocessing step in many multimedia and computer vision applications. Recently, de-blurring methods have been performed by neural network
Minsoo Hong, Yoonsik Choe
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