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Image Restoration from Parametric Transformations using Generative Models [article]

Kalliopi Basioti, George V. Moustakides
2020 arXiv   pre-print
When images are statistically described by a generative model we can use this information to develop optimum techniques for various image restoration problems as inpainting, super-resolution, image coloring  ...  image from a single mixture.  ...  Acknowledgment This work was supported by the US National Science Foundation under Grant CIF 1513373, through Rutgers University.  ... 
arXiv:2005.14036v2 fatcat:lu2rs2nvdnbffag6lgssj7x4wy

Deformable template models for emission tomography

Y. Amit, K.M. Manbeck
1993 IEEE Transactions on Medical Imaging  
Previous efforts to regularize the restoration process have incorporated rather general assumptions about the isotope distribution within a patient's body.  ...  Here we present a theoretical and algorithmic framework in which the notion of a deformable template can be used to identify and quantify brain tumors in pediatric patients.  ...  The restoration procedure consists of finding the transformation which minimizes the posterior. This transformation is then applied to the template in order to generate the restored image.  ... 
doi:10.1109/42.232254 pmid:18218413 fatcat:fkcq6nzl55bwlhmz72c3gup4eu

Efficient generalized cross-validation with applications to parametric image restoration and resolution enhancement

N. Nguyen, P. Milanfar, G. Golub
2001 IEEE Transactions on Image Processing  
We estimate these PSF parameters for this ill-posed class of inverse problem from raw data, along with the regularization parameters required to stabilize the solution, using the generalized cross-validation  ...  In many image restoration/resolution enhancement applications, the blurring process, i.e., point spread function (PSF) of the imaging system, is not known or is known only to within a set of parameters  ...  We enforce a parametric model upon the blurring process so that (1) becomes (6) (7) where the blurring operator is generated from a parameter set .  ... 
doi:10.1109/83.941854 pmid:18255545 fatcat:yttgxbcqingvxbx6yydt7uytje

Shearlet-Wavelet Regularized Semismooth Newton Iteration for Image Restoration

Liang Ding, Xueru Zhao
2015 Mathematical Problems in Engineering  
For the image restoration, this paper adopted a strategy of combined shearlet and wavelet frame and proposed a new restoration method.  ...  But the traditional wavelet or multidirectional wave (ridgelet, contourlet, curvelet, etc.) could only restore one of these structures efficiently so that the restoration results for complex images are  ...  Image restoration mainly includes parametric and nonparametric object models. There are plenty of literatures about nonparametric object models.  ... 
doi:10.1155/2015/647254 fatcat:zyrd46obs5arzdyru7t7d36njy

Functional Neural Networks for Parametric Image Restoration Problems [article]

Fangzhou Luo, Xiaolin Wu, Yanhui Guo
2021 arXiv   pre-print
In this work, we propose a novel system called functional neural network (FuncNet) to solve a parametric image restoration problem with a single model.  ...  The experimental results show the superiority of our FuncNet on all three parametric image restoration tasks over the state of the arts.  ...  It is a general image restoration method which can solve various image restoration problems with a single model, as long as the degradation model is continuously differentiable.  ... 
arXiv:2111.00361v1 fatcat:spwhilaotnduhfxikcsvdqhrty

Computer Modeling of an Image of the Optical-Electronic System for Reference Mark Position Control

Tuan Pham Ngoc, Aleksandr Vasilev, Alexander Timofeev, Valery Korotaev, Anton Maraev
2019 Majorov International Conference on Software Engineering and Computer Systems  
A general algorithm for reference mark image description taking into account its relative motion is presented. A numerical experiment of image restoration using Matlab is shown.  ...  It is demonstrated that, when information is processed by OES RMPC, image restoration algorithm by Wiener parametric filtration and Tikhonov regularization are the most effective.  ...  Computer model of the reference mark image To develop and study an image model of the RM as a light source, a mathematical model has been created, its general structure is shown in Fig. 1 .  ... 
dblp:conf/micsecs/NgocVTKM19 fatcat:wkhv6rk57jdrjhcckv3hppwb6y

Combined interpolation—restoration of Landsat images through FIR filter design techniques

1993 International Journal of Remote Sensing  
The experimental results consist of interpolation-restoration processes of Landsat-5 Thematic Mapper images from 30 m to 15 m (scale magnification) but they could also be generalized to include deblurring  ...  The ideal low pass FIR filter for interpolation is modified to account for the restoration process. The Modified Inverse Filter (MIF) and the Wiener Filter (WF) are used for this purpose.  ...  Banon for valuable discussions about the subject of image restoration.  ... 
doi:10.1080/01431169308904292 fatcat:x5j3ru6jljce3owhvw2l3lms7a


2000 International Journal of Neural Systems  
The nonlinear module is a semi-parametric expansion made up of two sub-networks, one of which is a linear model and the other of which is a three-layer perceptron.  ...  Any general nonlinear independent component analysis algorithm for such a problem should specify which solution it tries to find.  ...  Acknowledgments The work described in this paper was partially supported by a grant from the Hong Kong Polytechnic University (project no.  ... 
doi:10.1142/s0129065700000089 pmid:10939342 fatcat:qmcwwzlbtfchvausbmqh7c5z3i

Synthetic Aperture Radar Autofocus Based on a Bilinear Model

Kuang-Hung Liu, Ami Wiesel, David C. Munson
2012 IEEE Transactions on Image Processing  
Autofocus algorithms are used to restore images in nonideal synthetic aperture radar imaging systems.  ...  In this paper, we propose a bilinear parametric model for the unknown image and the nuisance phase parameters and derive an efficient maximum-likelihood autofocus (MLA) algorithm.  ...  Fig. 6 . 6 Model mismatching using rectangular kernel SNR dB : (a) Focused image using exact model; (b) focused image using mismatched model; (c) MLA restoration (phase MSE ); and (d) FMCA restoration  ... 
doi:10.1109/tip.2012.2183881 pmid:22249713 fatcat:wjwmiu25sfa7xhuercgx7ox7wu

A pipeline to improve compressed image quality

Jean-Marc Delvit, Carole Thiebaut, Christophe Latry, Gwendoline Blanchet, Roberto Camarero, Nikos Karafolas, Zoran Sodnik, Bruno Cugny
2019 International Conference on Space Optics — ICSO 2018  
This paper presents a new image restoration pipeline performing especially well on noisy and compressed images. Most images are corrupted by noise.  ...  We achieve better restoration than classical algorithms on satellite imagery. This improvement in image quality is shown on two kinds of application: pansharpening and 3D restitution.  ...  They are equal to 1 for a general use.  ... 
doi:10.1117/12.2536189 fatcat:qpzbg6xkcvgdre72nin4pa7prm

Parametric design in the restoration project

Luis Carlos Cruz Ramírez
2019 Gremium  
used to determine the necessary steps in the generation of the form.  ...  The objective of this article is to present the use of parametric design in the development of restoration projects.  ...  Parametric modeling is the generation of entities using parameters, which has a number of possibilities for generating and analyzing forms and models (Stavrić, Šiđanin, Tepavčević, 2003, p. 67) .  ... 
doaj:018f1be9e6ae47e4b5de9c1d2292c553 fatcat:jl3bzyd46fg4pmbs5muzgfbtzy

Close the loop: Joint blind image restoration and recognition with sparse representation prior

Haichao Zhang, Jianchao Yang, Yanning Zhang, Nasser M. Nasrabadi, Thomas S. Huang
2011 2011 International Conference on Computer Vision  
Treating restoration and recognition separately, such a straightforward approach, however, suffers greatly from the defective output of the illposed blind image restoration.  ...  Based on such a sparse representation prior, we demonstrate that the image restoration task and the recognition task can benefit greatly from each other.  ...  Instead of restoring the test image, another approach could be to estimate the degradation model first, use it to transform the training images, and then compare the input test image with the synthetically  ... 
doi:10.1109/iccv.2011.6126315 dblp:conf/iccv/ZhangYZNH11 fatcat:6u323ektdrarhixucayo3t3c5q

Face Hallucination: A Review

Jaskiran Kaur, Asst. Prof. Manish Mahajan
2014 International Journal of Engineering Trends and Technoloy  
Face hallucination is a technique of domain-specific super-resolution problem having goal to generate high-resolution images from low-resolution inputs, which finds numerous vision applications.  ...  In this paper, we study face hallucination which is the process of synthesizing a high-resolution face image from an input LR image, with the help of a large collection of other HR face images.  ...  In the paper [15] addressed that the objective presented in the work is the super-resolution restoration of a set of images, and they investigated the use of learnt image models within a generative Bayesian  ... 
doi:10.14445/22315381/ijett-v11p212 fatcat:pmdicmlewbfjjaqffxlx36rvjq

A recursive soft-decision approach to blind image deconvolution

K.-H. Yap, Ling Guan, Wanquan Liu
2003 IEEE Transactions on Signal Processing  
The approach integrates the knowledge of well-known blur models without compromising its flexibility in restoring images degraded by nonstandard blurs.  ...  A nested neural network, called the hierarchical cluster model is employed to provide an adaptive, perception-based restoration.  ...  model from the solution space .  ... 
doi:10.1109/tsp.2002.806985 fatcat:zkuepn5v7befdpfnix4shki4ba

Out-of-focus blur estimation for blind image deconvolution: Using particle swarm optimization

Tsung-Ying Sun, Sin-Jhe Ciou, Chan-Cheng Liu, Chih-Li Huo
2009 2009 IEEE International Conference on Systems, Man and Cybernetics  
To identify the blind image it is a very important step for restoring the image. Therefore, the first step is to look for PSF model.  ...  This study addresses the blind image deconvolution which uses only blurred image and less point spread function (PSF) information to restore the original image.  ...  Generally, a parametric blur model may be used. 2) Joint identification methods: with this approach, most of they use an alternative approach to estimate an original image and the PSF rather than truly  ... 
doi:10.1109/icsmc.2009.5346769 dblp:conf/smc/SunCLH09 fatcat:dpwag3qquvcp7eglpllxvfwa74
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