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Blind image deconvolution using a robust GCD approach
1999
IEEE Transactions on Image Processing
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We propose a new, fast, based on matrices of special form, method, deblurring the initial blurred image in a stable way, reducing per one order the required computational complexity. ...
In this paper, we study the problem of image deblurring which arises in Image Processing and Computer Graphics. More precisely, we study the deblurring of a blurred image in one and two dimensions. ...
We propose a new, fast, based on matrices of special form, method, deblurring the initial blurred image in a stable way, reducing per one order the required computational complexity. ...
doi:10.1109/83.743863
pmid:18267476
fatcat:fwslbne7rfhyjk33ezd7rhubky
Ringing Detector for Deblurring based on Frequency Analysis of PSF
2011
IPSJ Transactions on Computer Vision and Applications
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Many deblurring techniques have been proposed to restore blurred images resulting from camera motion. ...
Ringings are detected by evaluating whether the deblurred image contains sine waves corresponding to the null frequencies across the entire image with uniform phase. ...
Ac-1 http://www.flickr.com/
Application to Deblurring
Deblurring Using the Ringing Detector A deblurred image based on the inverse Fourier transformation is the sum of the original image and the error ...
doi:10.2197/ipsjtcva.3.236
fatcat:yateexo5k5by5mwfchfk4ojffa
UHD Image Deblurring via Multi-scale Cubic-Mixer
[article]
2022
arXiv
pre-print
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Currently, transformer-based algorithms are making a splash in the domain of image deblurring. ...
We term this deep network as Multi-scale Cubic-Mixer, which is acted on both the real and imaginary components after fast Fourier transform to estimate the Fourier coefficients and thus obtain a deblurred ...
These methods obtain Fourier coefficients by fast Fourier transform (FFT) to generate a sharp image with the deep network. However, there are two limitations to these frequency-based methods. ...
arXiv:2206.03678v1
fatcat:6qclyafqtzdnzb3q2nvpe6ytf4
Real-time Blind Deblurring Based on Lightweight Deep-Wiener-Network
[article]
2023
arXiv
pre-print
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2022 pre-print arXiv:2211.16356v1 fatcat:7y2swbousnftdn66bhvoocs3xeOther Versions
Two of our models can reach a speed of 100 images per second, which is qualified for real-time deblurring. Further research may focus on some real-world applications of deblurring with our models. ...
Experimental evaluations show that our approaches have an edge on State of the Art in terms of inference times and numbers of parameters. ...
Various effective GAN(generative adversarial network)based deblurring methods are also proposed to solve image deblurring problems. ...
arXiv:2211.16356v3
fatcat:wngppwmsencerkyrpqm3dxplha
Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring
[article]
2019
arXiv
pre-print
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Therefore, the estimation of the blur kernel is essentially important for blind image deblurring. ...
Our approach is evaluated extensively on synthetic and real data and shows good results compared to the state-of-the-art deblurring approaches. ...
Uniform Deblurring Based on the analysis of the Fourier theory of phase-only images, we introduce our approach to estimate the blur kernel and deblur the images. ...
arXiv:1811.10185v3
fatcat:xted4brixfejhpgufzpciwt4na
Phase-Only Image Based Kernel Estimation for Single Image Blind Deblurring
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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Therefore, the estimation of the blur kernel is essentially important for blind image deblurring. ...
Our approach is evaluated extensively on synthetic and real data and shows good results compared to the state-of-the-art deblurring approaches. ...
Uniform Deblurring Based on the analysis of the Fourier theory of phase-only images, we introduce our approach to estimate the blur kernel and deblur the images. ...
doi:10.1109/cvpr.2019.00619
dblp:conf/cvpr/PanHLD19
fatcat:mbv7uzwcxjhurkrgseczwmmx7a
A survey on image deblurring
2016
2016 International Conference on Computer Communication and Informatics (ICCCI)
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from each frame can be preferred through a weighted average in the Fourier Transform. ...
After the process of deblurring, the improved quality of the image is capable to spot the specific exposure time. ...
The noise removal mechanism, feature extraction using Scale Invariant Feature Transform technique, weighted Fourier transform. ...
doi:10.1109/iccci.2016.7479956
fatcat:dswfqan5e5d6jhm7wjw2f6yiha
Deblurring approach for motion camera combining FFT with α-confidence goal optimization
2020
Optica Applicata
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An accurate estimation method of point spread function is firstly developed by performing the Fourier transform twice. ...
The proposed deblurring approach is finally carried out on both the synthetic-blurred images and the real-scene images. ...
The RL method restores noise-free or small-noise blurred images based on Bayes' theorem at first. ...
doi:10.37190/oa200202
fatcat:bdjs7mfjs5eltnka5vafwfchvq
DAUBECHIES COMPLEX WAVELET TRANSFORM BASED MULTILEVEL SHRINKAGE FOR DEBLURRING OF MEDICAL IMAGES IN PRESENCE OF NOISE
2009
International Journal of Wavelets, Multiresolution and Information Processing
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In this paper, we propose a new method of image deblurring in presence of noise, using symmetric Daubechies complex wavelet transform. ...
The proposed method is based on shrinkage of multilevel Daubechies complex wavelet coefficients, and is adaptive as it uses shrinkage function based on the variance of wavelet coefficients as well as the ...
), 12 based on real wavelet transform. ...
doi:10.1142/s0219691309003100
fatcat:chsfgvo4ovcotpmup5s6iprbfm
Image deblurring using empirical Wiener filter in the curvelet domain and joint non-local means filter in the spatial domain
2013
Imaging Science Journal
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Although the curvelet-based methods are efficient in edge-preserving image denoising, they are prone to producing edge ringing which relates to the structure of the underlying curvelet. ...
In this paper, an efficient image deblurring algorithm is proposed. ...
of the curvelet transform in two dimensions. 5 The first digital transformation is based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected ...
doi:10.1179/1743131x12y.0000000040
fatcat:k5rw35o5ynfuvk4u3cquiwq67u
Influence of blur on feature matching and a geometric approach for photogrammetric deblurring
2014
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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In the study reported in this paper, overlapping images are used to support the deblurring process, which is advantageous. An algorithm based on the Fourier transformation is presented. ...
<br><br> The aim of this research is to develop a blur correction method to deblur UAV images. ...
The described approach here using Fourier transformation returns good deblurred result for flat areas. However, the dependency on sharp images for deblurring makes this approach difficult to apply. ...
doi:10.5194/isprsarchives-xl-3-321-2014
fatcat:3azrhf452zhvxcainb56x7uk54
Motion Deblurring for Single-Pixel Spatial Frequency Domain Imaging
2022
Applied Sciences
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On this basis, a motion-degradation-model-based compensation, which is derived by the phase-shift and frequency-shift properties of Fourier transform, is adopted to eliminate the effects of target displacements ...
In this method, the Fourier coefficients of the reflected image are measured by the Fourier single-pixel imaging technique. ...
On this basis, a motion-degradation-model-based compensation, which is derived by the phase-shift and frequency-shift properties of Fourier transform, is adopted to eliminate the effects of target displacements ...
doi:10.3390/app12157402
fatcat:famr3lbpkvha3hxjdlbxjn54h4
Uniform and Non-Uniform Single Image Deblurring Based on Sparse Representation and Adaptive Dictionary Learning
2014
The International Journal of Multimedia & Its Applications
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Considering the sparseness property of images, a sparse representation based iterative deblurring method is presented for single image deblurring under uniform and non-uniform motion blur. ...
The approach taken is based on sparse and redundant representations over adaptively training dictionaries from single blurred-noisy image itself. ...
Our proposed method based on sparse image modelling also shows comparable result to this method with less complexity. ...
doi:10.5121/ijma.2013.6104
fatcat:gnn7s3ovczhfnidi6cx7327x6q
Deblurring of class-averaged images in single-particle electron microscopy
2010
Inverse Problems
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This paper proposes a method for deblurring of class-averaged images in single-particle electron microscopy (EM). ...
, and Hermite expansion and Laguerre-Fourier expansion retain their structures under the Fourier transform. ...
Acknowledgments This work was supported by NIH Grant R01GM075310 "Group-Theoretic Methods in Protein Structure Determination." The authors would like to thank Dr. ...
doi:10.1088/0266-5611/26/3/035002
pmid:20221416
pmcid:PMC2835172
fatcat:hzdcxsdh2barzhs5xnmoain3qq
NBD-GAP: Non-Blind Image Deblurring Without Clean Target Images
[article]
2022
arXiv
pre-print
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In recent years, deep neural network-based restoration methods have achieved state-of-the-art results in various image deblurring tasks. ...
However, one major drawback of deep learning-based deblurring networks is that large amounts of blurry-clean image pairs are required for training to achieve good performance. ...
2 E|X| 2 , (6) where F denotes the Fourier transform. ...
arXiv:2209.09498v1
fatcat:457ov5t73ja4vn2fdg5tvg4yvq
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