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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2018-Jun-27
Clarivate Analytics published the InCites Journal Citations Report for 2017. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.699, and the JCR 5-Year Impact Factor is 0.674.

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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  2/2018 - 10

Maximum Entropy Principle in Image Restoration

PETROVICI, M.-A. See more information about PETROVICI, M.-A. on SCOPUS See more information about PETROVICI, M.-A. on IEEExplore See more information about PETROVICI, M.-A. on Web of Science, DAMIAN, C. See more information about  DAMIAN, C. on SCOPUS See more information about  DAMIAN, C. on SCOPUS See more information about DAMIAN, C. on Web of Science, COLTUC, D. See more information about COLTUC, D. on SCOPUS See more information about COLTUC, D. on SCOPUS See more information about COLTUC, D. on Web of Science
 
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Download PDF pdficon (1,473 KB) | Citation | Downloads: 158 | Views: 303

Author keywords
image processing, image reconstruction, image representation, image restoration, image sampling

References keywords
entropy(20), maximum(18), image(13), reconstruction(7), method(6), methods(5), data(5), astronomical(5), restoration(4), imaging(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2018-05-31
Volume 18, Issue 2, Year 2018, On page(s): 77 - 84
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2018.02010
Web of Science Accession Number: 000434245000010
SCOPUS ID: 85047876823

Abstract
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Many imaging systems are faced with the problem of estimating a true image from a degraded dataset. In such systems, the image degradation is translated into a convolution with a Point Spread Function (PSF) and addition of noise. Often, the image recovery by inverse filtering is not possible because the PSF matrix is ill-conditioned. Maximum Entropy (MaxEnt) is an alternative method, which uses the entropy concept for estimating the true image. This paper presents MaxEnt method, starting with the historical references of the entropy concept and finalizing with its application in image restoration and reconstruction. The statistical model of MaxEnt for images is discussed and the connection of MaxEnt with the Bayesian inference is explained. MaxEnt is evaluated by using a modified version of Cornwell algorithm. Two cases are considered: images degraded by various PSF kernels in presence of additive noise and images resulted from incomplete datasets. The tests show PSNR gains ranging from 1 to 7dB for the degraded images and images reconstructed at 25dB from datasets with up to 80% missing pixels.


References | Cited By  «-- Click to see who has cited this paper

[1] J.-L. Starck, F. Murtagh, "Astronomical image and data analysis", pp.71-110, Springer Science & Business Media, 2007,
[CrossRef]


[2] A. Giffin, "Maximum entropy: the universal method for inference", pp. 20-25, ProQuest, Umi Dissertation Publishing, 2011.

[3] C. Shannon, "A mathematical theory of communication." Bell System Technical Journal, no.27, pp. 379-423, 1948,
[CrossRef] [SCOPUS Times Cited 11438]


[4] E. T. Jaynes, "Information theory and statistical mechanics." Physical review, no.106, p. 620, 1957,
[CrossRef] [SCOPUS Times Cited 5915]


[5] B. R. Frieden, "Restoring with Maximum Likelihood and Maximum Entropy", JOSA, no.62, pp.511-518, 1972,
[CrossRef] [SCOPUS Times Cited 444]


[6] S. F. Gull, G. J. Daniell,"Image reconstruction from incomplete and noisy data. " Nature, no. 272, pp. 686-690, 1978,
[CrossRef] [Web of Science Times Cited 793] [SCOPUS Times Cited 676]


[7] J. Skilling , "Maximum Entropy and Bayesian Methods", Kluwer, pp. 45-52, 1989,
[CrossRef]


[8] N. Weir, "A multi-channel method of maximum entropy image restoration". Astronomical Data Analysis Software and Systems I, vol. 25, p. 186, 1992.

[9] Tj. R. Bontekoe, E. Koper, and D. J. M. Kester, "Pyramid maximum entropy images of IRAS survey data.", Astronomy and Astrophysics no.284, pp.1037-1053, 1994.

[10] E. Pantin, J. L. Starck, "Deconvolution of astronomical images using the multiscale maximum entropy method. ", Astronomy and Astrophysics Supplement Series, no. 118, pp. 575-585, 1996,
[CrossRef]


[11] J. Guan, L. M. Song, Z. X. Huo, "Application of a multiscale maximum entropy image restoration algorithm to HXMT observations. " Chinese physics C, pp. 0-0, 2016,
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[12] B. Zhao, G. Qin, P.Liu, "A Robust Image Tampering Detection Method Based on Maximum Entropy Criteria." Entropy 17.12 , 2015 , pp. 7948-7966,
[CrossRef] [Web of Science Times Cited 2] [SCOPUS Times Cited 2]


[13] M. Willis, B. D. Jeffs, D. G. Long, "A new look at maximum entropy image reconstruction." Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on. IEEE, vol. 2, pp. 1272-1276, 1999,
[CrossRef] [SCOPUS Times Cited 3]


[14] J. Skilling, R. Bryan, "Maximum entropy image reconstruction: general algorithm. " Monthly notices of the royal astronomical society, no. 211, pp.111-124, 1984,
[CrossRef] [Web of Science Times Cited 760]


[15] A. Caticha, A. Giffin, "Updating probabilities." AIP Conference Proceedings, vol. 872, no. 1. AIP, 2006,
[CrossRef] [SCOPUS Times Cited 74]


[16] E. T. Jaynes, "On the rationale of maximum-entropy methods. " Proceedings of the IEEE, no. 70, pp. 939-952, 1982,
[CrossRef] [Web of Science Times Cited 787] [SCOPUS Times Cited 867]


[17] A. Jannetta, J. C. Jackson, C. J. Kotre, I. P. Birch, K. J. Robson, R. Padgett, "Mammographic image restoration using maximum entropy deconvolution. " Physics in Medicine and Biology, no. 49, p. 4997, 2004,
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 9]


[18] M. K. Charter, W. T. Grandy Jr, L. H. Schick, "Maximum Entropy and Bayesian Methods.", ed. PF Fougere, pp. 325-339, Dordrecht: Kluwer, 1990,
[CrossRef]


[19] B. R. Frieden, "Image enhancement and restoration." Picture Processing and Digital Filtering. Springer Berlin Heidelberg, pp.177-248, 1975,
[CrossRef]


[20] T. Cornwell, K. Evans, "A simple maximum entropy deconvolution algorithm." Astronomy and Astrophysics, no.143, pp. 77-83, 1985.

[21] N. I. Gould, S. Leyffer, "An introduction to algorithms for nonlinear optimization." Frontiers in numerical analysis. Springer Berlin Heidelberg, pp. 109-197, 2003,
[CrossRef]


[22] A. Mohammad-Djafari,"Entropy, information theory, information geometry and Bayesian inference in data, signal and image processing and inverse problems." Entropy no.17.6, pp. 3989-4027, 2015,
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 15]


[23] K. Maisinger, M. P. Hobson, A. N. Lasenby , "Maximum-entropy image reconstruction using wavelets. " Monthly Notices of the Royal Astronomical Society, no. 347(1), pp. 339-354, 2004,
[CrossRef] [Web of Science Times Cited 30] [SCOPUS Times Cited 32]


[24] T. Hedrich, et al. , "Comparison of the spatial resolution of source imaging techniques in high-density EEG and MEG." NeuroImage, no.157, pp. 531-544, 2017,
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 12]


[25] J. J. Martín-Sotoca, A. Saa-Requejo, J. B. Grau, A. Paz-González, A. M. Tarquis,, "Combining global and local scaling methods to detect soil pore space." Journal of Geochemical Exploration, vol. 189, pp. 72-84, 2018,
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 2]


[26] D. Gagliardi, et al., "Estimation of the effective bone-elasticity tensor based on µCT imaging by a stochastic model. A multi-method validation." European Journal of Mechanics-A/Solids, vol. 69, pp. 147-167, 2018,
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[27] Y. Li, et al., "Characterization of macropore structure of Malan loess in NW China based on 3D pipe models constructed by using computed tomography technology." Journal of Asian Earth Sciences, vol. 154, pp. 271-279, 2018,
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 4]


[28] Q. L. Yu, et al., "Transverse phase space reconstruction study in Shanghai soft X-ray FEL facility." Nuclear Science and Techniques, vol. 29, no. 1, 2018,
[CrossRef] [Web of Science Times Cited 1] [SCOPUS Times Cited 1]


[29] J. B.Heymann, "Tomographic Reconstruction from Electron Micrographs." Cellular Imaging. Springer, Cham, pp. 209-236, 2018,
[CrossRef]


[30] S. Shentu, et al., "Maximum entropy method for ocean acoustic tomography." Signal Processing, Communications and Computing (ICSPCC), 2017 IEEE International Conference on. IEEE, 2017,
[CrossRef] [SCOPUS Times Cited 1]


[31] M. A. Petrovici, C. Damian, D. Coltuc, "Image reconstruction from incomplete measurements: Maximum Entropy versus L1 norm optimization." Signals, Circuits and Systems (ISSCS), 2017 International Symposium on. IEEE, 2017,
[CrossRef] [SCOPUS Times Cited 1]


[32] H. Costin, S. Bejinariu, D. Costin, "Biomedical Image Registration by means of Bacterial Foraging Paradigm", International Journal of Computers, Communications & Control (IJCCC), vol. 11, no. 3, pp. 329-345, 2016,
[CrossRef] [Web of Science Times Cited 2]


[33] G. Steidl, T. Teuber, "Removing multiplicative noise by Douglas-Rachford splitting methods", Journal of Mathematical Imaging and Vision, vol. 36, no.2, pp.168-184, 2010,
[CrossRef] [Web of Science Times Cited 144] [SCOPUS Times Cited 159]


[34] G. Aubert, J. F. Aujol, "A variational approach to removing multiplicative noise", SIAM Journal on Applied Mathematics, vol.68, no.4, pp.925-946, 2008,
[CrossRef] [Web of Science Times Cited 245] [SCOPUS Times Cited 291]




References Weight

Web of Science® Citations for all references: 2,795 TCR
SCOPUS® Citations for all references: 19,948 TCR

Web of Science® Average Citations per reference: 80 ACR
SCOPUS® Average Citations per reference: 570 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2018-11-16 21:53 in 212 seconds.




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