Results 21 to 30 of about 4,574 (198)
Blind Image Deblurring: a Review
CoRR, 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 ...
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A Blur Restoration Algorithm Based on L0 Regularization [PDF]
Jisuanji gongcheng, 2016 Aiming at the motion blur,a new blind deblurring algorithm is proposed,which is based on the L0 regularization restraints and the prior knowledge of natural image gradient distribution to obtain the real motion kernel.In the proposed methods,T-smooth ...
FANG Shuai,FAN Dong,YU Lei,CAO Fengyun
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Blind Text Image Deblurring Algorithm Based on Multi-Scale Fusion and Sparse Priors
IEEE Access, 2023 The goal of blind text image deblurring is to obtain a clean text image from the given blurry text image without knowing the blur kernel. Sparsity-based methods have been shown their effectiveness in various blind text image deblurring models.
Zhe Li +3 more
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Learning Wavefront Coding for Extended Depth of Field Imaging [PDF]
, 2020 Depth of field is an important factor of imaging systems that highly affects the quality of the acquired spatial information. Extended depth of field (EDoF) imaging is a challenging ill-posed problem and has been extensively addressed in the literature ...
Akpinar, Ugur +4 more
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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
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Burst Ranking for Blind Multi-Image Deblurring [PDF]
IEEE Transactions on Image Processing, 2020 We propose a new incremental aggregation algorithm for multi-image deblurring with automatic image selection. The primary motivation is that current bursts deblurring methods do not handle well situations in which misalignment or out-of-context frames are present in the burst.
Fidel Alejandro Guerrero Peña +4 more
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CoRR, 2019 Deblurring is the task of restoring a blurred image to a sharp one, retrieving the information lost due to the blur. In blind deblurring we have no information regarding the blur kernel. As deblurring can be considered as an image to image translation task, deep learning based solutions, including the ones which use GAN (Generative Adversarial Network),
Manoj Kumar Lenka +2 more
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Blind deblurring of foreground-background images [PDF]
2009 16th IEEE International Conference on Image Processing (ICIP), 2009 This paper presents a method for deblurring an image consisting of two layers (a foreground layer and a background layer) which have suffered different, unknown blurs. This is a situation of practical interest. For example, it is common to find images in which we have a foreground object (e.g. a car) which has motion blur while the background is sharp (
Mariana S. C. Almeida, Luís B. Almeida
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Hyper-Laplacian Regularized Non-Local Low-Rank Prior for Blind Image Deblurring
IEEE Access, 2020 Blind deblurring of single image is a challenging image restoration problem. Recent various image priors have been successfully explored to solve this ill-posed problem. In this paper, based on the non-local self-similarity, we propose a novel method for
Xiaole Chen +5 more
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IEEE Access, 2020 Blind image deblurring, composed of estimating blur kernel and non-blind deconvolution, is an extremely ill-posed problem. However, previous deblurring methods still cannot solve delta kernel or noise problem well and avoid ringing artifacts in restored ...
Hongtian Zhao +3 more
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