Results 31 to 40 of about 615,528 (247)
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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Analyzing spatially-varying blur [PDF]
, 2010 Blur is caused by a pixel receiving light from multiple scene points, and in many cases, such as object motion, the induced blur varies spatially across the image plane.
William T. Freeman +5 more
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Classifying Discriminative Features for Blur Detection
, 2016 Blur detection in a single image is challenging especially when the blur is spatially-varying. Developing discriminative blur features is an open problem. In this paper, we propose a new kernel-specific feature vector consisting of the information of a
Pang, YW +4 more
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Image Blind Deblurring Using an Adaptive Patch Prior
Tsinghua Science and Technology, 2019 Image blind deblurring uses an estimated blur kernel to obtain an optimal restored original image with sharp features from a degraded image with blur and noise artifacts.
Yongde Guo, Hongbing Ma
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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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Space-variant blur kernel estimation and image deblurring through kernel clustering
, 2019 This paper presents a space-variant blur kernel estimation and image deblurring framework. For space-variant blur kernel estimation, the input image is divided into small patches, and for each patch, the blur kernel is estimated.
Güntürk, Bahadır Kürşat +2 more
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Image Invariants to Anisotropic Gaussian Blur [PDF]
, 2019 The paper presents a new theory of invariants to Gaussian blur. Unlike earlier methods, the blur kernel may be arbitrary oriented, scaled and elongated.
Jan Flusser +7 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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A motion parameters estimating method based on deep learning for visual blurred object tracking
IET Image Processing, 2021 Tracking the specific object in the blurred scenes is one of the challenging problems in computer vision and image processing. The accuracy and performance of trackers within the blur frames usually demonstrate a severe decrease.
Iman Iraei, Karim Faez
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Mathematical Problems of Computer Science, 2021 In this paper, we present deep learning-based blind image deblurring methods for estimating and removing a non-uniform motion blur from a single blurry image. We propose two fully convolutional neural networks (CNN) for solving the problem.
Misak T. Shoyan +2 more
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