Results 11 to 20 of about 4,539 (201)
Stochastic Blind Motion Deblurring [PDF]
IEEE Transactions on Image Processing, 2015 Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can, therefore, only be obtained with the help of prior information in the form of (often nonconvex) regularization terms for both the intrinsic image and the kernel.
Xiao, Lei +3 more
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Infrared Image Deblurring Based on Generative Adversarial Networks
International Journal of Optics, 2021 Blind deblurring of a single infrared image is a challenging computer vision problem. Because the blur is not only caused by the motion of different objects but also by the relative motion and jitter of cameras, there is a change of scene depth.
Yuqing Zhao +4 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 Pena +4 more
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Recovering Blurred Images to Recognize Field Information
Proceedings, 2022 This paper introduces a new computational approach for fast deblurring non-blind imaging. The method implementation reveals how to solve image deblurring integrals with arbitrary kernels using the Theory of Hypernumbers. The method is applicable for real-
Arkadiy Dantsker
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MedDeblur: Medical Image Deblurring with Residual Dense Spatial-Asymmetric Attention
Mathematics, 2022 Medical image acquisition devices are susceptible to producing blurry images due to respiratory and patient movement. Despite having a notable impact on such blind-motion deblurring, medical image deblurring is still underexposed.
S. M. A. Sharif +5 more
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Discriminative Non-blind Deblurring [PDF]
2013 IEEE Conference on Computer Vision and Pattern Recognition, 2013 Non-blind deblurring is an integral component of blind approaches for removing image blur due to camera shake. Even though learning-based deblurring methods exist, they have been limited to the generative case and are computationally expensive. To this date, manually-defined models are thus most widely used, though limiting the attained restoration ...
Uwe Schmidt +4 more
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A Single Image Deblurring Approach Based on a Fractional Order Dark Channel Prior
International Journal of Applied Mathematics and Computer Science, 2022 The dark channel prior has been successfully applied to solve the blind deblurring problem on different scene images. Since the dark channel of the blurry-noise image is similar to that of the corresponding clear image, the sparsity of the dark channel ...
Yu Xiaoyuan, Xie Wei, Yu Jinwei
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An image defocus deblurring method based on gradient difference of boundary neighborhood
Virtual Reality & Intelligent Hardware, 2023 Background: For static scenes with multiple depth layers, the existing defocused image deblurring methods have the problems of edge ringing artifacts or insufficient deblurring degree due to inaccurate estimation of blur amount, In addition, the prior ...
Junjie TAO +6 more
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Image Deblurring Based on Residual Attention and Multi-feature Fusion [PDF]
Jisuanji kexue, 2023 Non-uniform blind deblurring in dynamic scenes is a challenging computer vision problem.Although deblurring algorithms based on deep learning have made great progress,there are still problems such as incomplete deblurring and loss of details.To solve ...
ZHAO Qian, ZHOU Dongming, YANG Hao, WANG Changchen
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COMBINED PATCH-WISE MINIMAL-MAXIMAL PIXELS REGULARIZATION FOR DEBLURRING [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Deblurring is a vital image pre-processing procedure to improve the quality of images. It is a classical ill-posed problem. A new blind deblurring method based on image sparsity prior is proposed here.
J. Han, S. L. Zhang, Z. Ye
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