Results 31 to 40 of about 36,154 (265)
Solar Speckle Image Deblurring With Deep Prior Constraint Based on Regularization
IEEE Access, 2022 The solar speckle image has the characteristics with single features, more noise, and blurred local details. Most of the existing deep learning deblurring methods for solar speckle images have some problems, such as high-frequency loss, artifact ...
Yahui Jin +5 more
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Blur kernel estimation of noisy-blurred image via dynamic structure prior
Neurocomputing, 2020 Abstract An accurate blur kernel is key to blind image deblurring and kernel estimation heavily relies on strong edges in the observed image [ 1 , 2, 3]. Previous methods [4] [5] leveraging image gradient prior with i.i.d statistics can hardly restrict strong edges in a noisy-blurred image, since both noise and strong edges are presented as strong ...
Xueling Chen +4 more
openaire +2 more sources
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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Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal [PDF]
, 2015 In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image. We propose a deep learning approach to predicting the probabilistic distribution of motion blur at the patch level using a convolutional ...
Cao, Wenfei +3 more
core +5 more sources
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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Deblurring by Realistic Blurring
, 2020 Existing deep learning methods for image deblurring typically train models using pairs of sharp images and their blurred counterparts. However, synthetically blurring images do not necessarily model the genuine blurring process in real-world scenarios ...
Li, Hongdong +6 more
core +1 more source
Explore Image Deblurring via Blur Kernel Space
CoRR, 2021 Accepted to CVPR ...
Phong Tran +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
doaj +1 more source