Filters








6,857 Hits in 7.7 sec

Bayesian Approach to Limited-Angle Reconstruction in Computed Tomography [chapter]

Kenneth M. Hanson, George W. Wecksung
1987 Maximum-Entropy and Bayesian Spectral Analysis and Estimation Problems  
The null-space components of deterministic solutions are usually zero, giving rise to unavoidable artifacts.  ...  There exists a null subspace in the Hilbert space of possible source functions about which the available projection measurements provide no information.  ...  Thus the concept of null space and the Bayesian methods proposed for overcoming its limitations are relevant to a large variety of image-restoration problems.  ... 
doi:10.1007/978-94-009-3961-5_15 fatcat:5n2jkljfn5dxbnf5aezuuxyaci

Bayesian approach to limited-angle reconstruction in computed tomography

Kenneth M. Hanson, George W. Wecksung
1983 Journal of the Optical Society of America  
The null-space components of deterministic solutions are usually zero, giving rise to unavoidable artifacts.  ...  There exists a null subspace in the Hilbert space of possible source functions about which the available projection measurements provide no information.  ...  Thus the concept of null space and the Bayesian methods proposed for overcoming its limitations are relevant to a large variety of image-restoration problems.  ... 
doi:10.1364/josa.73.001501 fatcat:tfy2bwgib5hcrbglr65pvndmfa

Ghost images and feasibility of reconstructions with the Richardson-Lucy algorithm

Jorge Llacer, Jorge Nunez, Timothy J. Schulz, Donald L. Snyder
1994 Image Reconstruction and Restoration  
The question was: What is the null space (ghost images) of the Richardson-Lucy (RL) algorithm?.  ...  We introduce the concept of a "nearly null" space, with an unsharp distinction between the "measurement" and the "null" components of an image and generate a reduced resolution Hubble Point Spread Function  ...  INTRODUCTION In the workshop on "The Restoration of HST Images and Spectra II" that took place at the Space Telescope Science Institute in November 1993, a question was raised as to what is the null space  ... 
doi:10.1117/12.188042 fatcat:vr4puhf6xrawlbpt5237pc466i

Iterative statistical approach to blind image deconvolution

Edmund Y. Lam, Joseph W. Goodman
2000 Optical Society of America. Journal A: Optics, Image Science, and Vision  
To facilitate computation we use an iterative method, which is an extension of the traditional expectation-maximization method, instead of direct optimization.  ...  We employ a statistical point of view of the data and use a modified maximum a posteriori approach to identify the most probable object and blur given the observed image.  ...  For image restoration, it could lead to better results because we can restore the portion of the object in the null space of the blur. 16 It could also lead to faster convergence as the prior knowledge  ... 
doi:10.1364/josaa.17.001177 pmid:10883969 fatcat:j2n7aweunjbnbnwtn5efyvo5yu

Multichannel blind deconvolution of spatially misaligned images

F. Sroubek, J. Flusser
2005 IEEE Transactions on Image Processing  
Index Terms-Image restoration, maximum a posteriori (MAP) estimator, multichannel blind deconvolution, subspace methods, variational integral.  ...  This stochastic approach enables us to recover the blurs and the original image from channels severely corrupted by noise.  ...  [21] , [22] suggested two MC restoration algorithms that, contrary to the previous two indirect algorithms, estimate directly the original image from the null space or from the range of a special matrix  ... 
doi:10.1109/tip.2005.849322 pmid:16028551 fatcat:mbdaswcmi5fkbmrop35ezcxoru

Interval estimate with probabilistic background constraints in deconvolution

Zhuo-xi Huo, Jian-feng Zhou
2012 Optical Society of America. Journal A: Optics, Image Science, and Vision  
Confidence intervals reveal the uncertainties due to the background constraint are calculated and significance levels for sources retrieved from restored images are provided.  ...  We elaborate our objective -- the interval estimate of the unknown object from observed data and our approach -- monte-carlo experiment and analysis of marginal distributions of image values.  ...  While in Bayesian statistics the maximum a posteriori (MAP) algorithm maximizes the conditional probability density of the object intensity to achieve a MAP estimate [11] .  ... 
doi:10.1364/josaa.29.002688 pmid:23455920 fatcat:kfo5gmlembcnjezbkoi2byijzy

Enhanced fog detection and free-space segmentation for car navigation

Nicolas Hautière, Jean-Philippe Tarel, Houssam Halmaoui, Roland Brémond, Didier Aubert
2011 Machine Vision and Applications  
Then, the method restores the contrast of the road by only assuming that the road is flat and, at the same time, detects the vertical objects.  ...  The proposed method is complementary to existing free-space area detection methods relying on color segmentation and stereovision.  ...  This is especially the case on the sidewalks and curbs which are detected as a part of the free-space area by the algorithm (see Fig. 14c for example), which was expected due to the definition chosen  ... 
doi:10.1007/s00138-011-0383-3 fatcat:sdov4uljirfgpjc4x7cy66qqyy

Spatio-temporal fMRI analysis using Markov random fields

X. Descombes, F. Kruggel, D.Y. Von Cramon
1998 IEEE Transactions on Medical Imaging  
Index Terms-Bayesian framework, functional magnetic resonance imaging (fMRI) analysis, Markov random fields (MRF's), signal analysis, signal restoration.  ...  We propose to embed the fMRI analysis problem into a Bayesian framework consisting of two steps: i) data restoration and ii) data analysis.  ...  This affine transformation is estimated by maximizing the image cross correlation [32] with the Simplex algorithm.  ... 
doi:10.1109/42.746636 pmid:10048860 fatcat:5hkmpunh7vcdncr3lyruqars4m

A recursive soft-decision approach to blind image deconvolution

K.-H. Yap, Ling Guan, Wanquan Liu
2003 IEEE Transactions on Signal Processing  
An optimization scheme is developed where a new cost function is projected and minimized with respect to the image and blur domains.  ...  This paper presents a new approach to blind image deconvolution based on soft-decision blur identification and hierarchical neural networks.  ...  Expectation maximization (EM) is often used in conjunction with ML to maximize the log-likelihood function of the parameter set from their solution spaces.  ... 
doi:10.1109/tsp.2002.806985 fatcat:zkuepn5v7befdpfnix4shki4ba

Bayesian and regularization methods for hyperparameter estimation in image restoration

R. Molina, A.K. Katsaggelos, J. Mateos
1999 IEEE Transactions on Image Processing  
We show analytically that the analysis provided by the evidence approach is more realistic and appropriate than the MAP approach for the image restoration problem.  ...  In this paper, we propose the application of the hierarchical Bayesian paradigm to the image restoration problem.  ...  The initial restoration for the MAP algorithm was the EM solution for the 10, 20, and 30 dB problems, respectively.  ... 
doi:10.1109/83.743857 pmid:18267470 fatcat:njm2cxjglffethnsqpxyzigto4

Fast and efficient MRF-based blotch detection algorithm for degraded film sequences

Sang-Churl Nam, Masahide Abe, Masayuki Kawamata
2007 2007 International Symposium on Intelligent Signal Processing and Communication Systems  
detection algorithms.  ...  This paper proposes an efficient blotch detection algorithm based on a Markov Random Field (MRF) model with less computational complexity and with lower false alarm rate than the existing MRF-based blotch  ...  detection r c and false alarm r f are defined as [1] : r c = C b N c , r f = F b N 1 N 2 − N c . (9) In our experiment, the search space used for the full search block matching algorithm was ±5 pixels  ... 
doi:10.1109/ispacs.2007.4445833 fatcat:th7s3cfjgzhlzkoyaadoqhx6we

Space-variant generalised Gaussian regularisation for image restoration

A. Lanza, S. Morigi, M. Pragliola, F. Sgallari
2018 Computer Methods in Biomechanics and Biomedical Engineering Imaging & Visualization  
The restored image is efficiently computed by means of an iterative numerical algorithm based on the alternating direction method of multipliers.  ...  We propose a new space-variant regularization term for variational image restoration based on the assumption that the gradient magnitudes of the target image distribute locally according to a half-Generalized  ...  Acknowledgments: Research was supported by the "National Group for Scientific Computation (GNCS-INDAM)" and by ex60 project by the University of Bologna "Funds for selected research topics".  ... 
doi:10.1080/21681163.2018.1471620 fatcat:rw4gqzdx7fhn7ndkfbacfcr3ha

Blur identification by residual spectral matching

A.E. Savakis, H.J. Trussell
1993 IEEE Transactions on Image Processing  
The PSF estimate is selected to provide the best match between the restoration residual power spectrum and its expected value, derived under the assumption that the candidate PSF is equal to the true PSF  ...  The a priori knowledge required is the noise variance and the original image spectrum.  ...  The Expectation-Maximization (EM) algorithm has been applied in the space [ l l ] and frequency domain [12] for iterative maximization of the likelihood function.  ... 
doi:10.1109/83.217219 pmid:18296204 fatcat:kc2vf25zb5hjzds53oiz6bljbu

Speckle Control with a Remapped-Pupil PIAA Coronagraph

Frantz Martinache, Olivier Guyon, Christophe Clergeon, Celia Blain
2012 Publications of the Astronomical Society of the Pacific  
, and demonstrate the benefit of the PIAA for high contrast imaging at small angular separation.  ...  The PIAA is a now well demonstrated high contrast technique that uses an intermediate remapping of the pupil for high contrast coronagraphy (apodization), before restoring it to recover classical imaging  ...  Using an iterative speckle nulling algorithm, the voltage map that cancels speckles within the control region of the DM has been identified.  ... 
doi:10.1086/668848 fatcat:hkbzq7pfwvesrb5rqhc3z3bxgm

Fast Blotch Detection Algorithm for Degraded Film Sequences Based on MRF Models

Sang-Churl Nam, Masahide Abe, Masayuki Kawamata
2007 2007 IEEE International Conference on Image Processing  
This paper proposes a fast blotch detection algorithm based on a Markov Random Field (MRF) model with less computational load and with lower false alarm rate than the existing MRF-based algorithms.  ...  The experimental results show that our proposed method provides the computational simplicity and an efficient detecting performance for the blotches.  ...  In our experiment, the search space used for the full search block matching algorithm was ±5 pixels. A block size of 8 × 8 was used.  ... 
doi:10.1109/icip.2007.4379371 dblp:conf/icip/NamAK07 fatcat:ixrlvzvkjbawhcxtoo7wkmfzxm
« Previous Showing results 1 — 15 out of 6,857 results