Results 41 to 50 of about 557,712 (297)
Robust Image Restoration for Motion Blur of Image Sensors
Sensors, 2016 Blind image restoration algorithms for motion blur have been deeply researched in the past years. Although great progress has been made, blurred images containing large blur and rich, small details still cannot be restored perfectly.
Fasheng Yang +4 more
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A New Full-Reference Image Quality Metric for Motion Blur Profile Characterization
IEEE Access, 2021 Motion blur is common in images captured by handheld devices, arising from hand, device and/or object motion. To restore sharp images from the images degraded by the motion, it is extremely important to assess the quality of the captured image and its ...
Mohammad Abdullah-Al-Mamun +2 more
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Text Image Deblurring Using Kernel Sparsity Prior [PDF]
, 2018 Previous methods on text image motion deblurring seldom consider the sparse characteristics of the blur kernel. This paper proposes a new text image motion deblurring method by exploiting the sparse properties of both text image itself and kernel.
Fang, Xianyong +4 more
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Blind image deblurring method based on
Journal of Measurement Science and Instrumentation, 2023 Aiming at the problem of ringing artifacts existing in the edge of image in traditional blind image deblurring methods, l1/l2 regularization-based blind image deblurring method is proposed. The latent image is constrained by l1/l2 regularization, and the
CAO Shengfang, HU Hongping, WANG Wenke
doaj
Concurrent Video Denoising and Deblurring for Dynamic Scenes
IEEE Access, 2021 Dynamic scene video deblurring is a challenging task due to the spatially variant blur inflicted by independently moving objects and camera shakes. Recent deep learning works bypass the ill-posedness of explicitly deriving the blur kernel by learning ...
Efklidis Katsaros +3 more
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Explore Image Deblurring via Blur Kernel Space
, 2021 Accepted to CVPR ...
Tran, Phong +3 more
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Blur Unblurred—A Mini Tutorial
i-Perception, 2018 Optical blur from defocus is quite frequently considered as equivalent to low-pass filtering. Yet that belief, although not entirely wrong, is inaccurate.
Hans Strasburger +2 more
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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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Blind Image Deblurring via Reweighted Graph Total Variation
, 2017 Blind image deblurring, i.e., deblurring without knowledge of the blur kernel, is a highly ill-posed problem. The problem can be solved in two parts: i) estimate a blur kernel from the blurry image, and ii) given estimated blur kernel, de-convolve blurry
Bai, Yuanchao +3 more
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Blur-Kernel Estimation from Spectral Irregularities [PDF]
, 2012 We describe a new method for recovering the blur kernel in motion-blurred images based on statistical irregularities their power spectrum exhibits. This is achieved by a power-law that refines the one traditionally used for describing natural images.
Amit Goldstein, Raanan Fattal
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