nach oben

Erschienen in:

2015 | OriginalPaper | Buchkapitel

Poisson Noise Removal from Mammogram Using Poisson Unbiased Risk Estimation Technique

verfasst von : Manas Saha, Mrinal Kanti Naskar, Biswa Nath Chatterji

Erschienen in: Information Systems Design and Intelligent Applications

Verlag: Springer India

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

We present an experimental work on the denoising of mammogram with Poisson noise. Reviewing the literature, it is found that the denoising performance of the multiresolution tools like wavelet, contourlet and curvelet implemented on mammogram with Poisson noise is unique. The first part of the investigation deals with the confirmation of this exceptional performance with our result. The later half implements the recently developed denoising approach called the Poisson Unbiased Risk Estimation-Linear Expansion of Thresholds (PURE-LET) to the Poisson noise corrupted mammogram with an objective to improve the peak signal to noise ratio (PSNR) further. The PURE-LET successfully removes Poisson noise better than the traditional mathematical transforms already mentioned. The computation time and PSNR are also evaluated in the perspective of the cycle spinning technique. This validates the applicability and efficiency of the novel denoising strategy in the field of digital mammography.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Vorheriges Kapitel Automatic Generation of Web Service Composition Templates Using WSDL Descriptions

Nächstes Kapitel A Proposed Systematic User-Interface Design Framework for Synchronous and Asynchronous E-Learning Systems

Naveed, N., Hussain, A., Arfan, M.J., Choi, T.S.: Quantum and impulse noise filtering from breast mammogram images. Comput. Methods Programs Biomed. 108(3), 1062–1069 (2012)CrossRef

Görgel, P., Sertbas, A., Ucan, O.N.: A wavelet-based mammographic image denoising and enhancement with homomorphic filtering. J. Med. Syst. 34(6), 993–1002 (2010)CrossRef

Mencattini, A., Rabottino, G., Salmeri, M., Lojacono, R.: Denoising and enhancement of mammographic images under the assumption of heteroscedastic additive noise by an optimal subband thresholding. Int. J. Wavelets Multiresolut. Inf. Process. 8(5), 713–774 (2010)MathSciNetCrossRefMATH

Görgel, P., Sertbas, A., Ucan, O.N.: Mammographical mass detection and classification using local seed region growing-spherical wavelet transform (LSRG-SWT) hybrid scheme. Comput. Biol. Med. 43(6), 765–774 (2013)CrossRef

Eltoukhy, M.M., Faye, I., Samir, B.B.: A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram. Comput. Biol. Med. 40(4), 384–391 (2010)CrossRef

Malar, E., Kandaswamy, A., Kirthana, S.S., Nivedhtha, D., Gauthaam, M.: Curvelet image denoising of mammogram images. Int. J. Med. Eng. Inf. 5(1), 60–67 (2013)

Malar, E., Kandaswamy, A., Kirthana, S.S., Nivedhitha, D.: A comparative study on mammographic image denoising technique using wavelet, curvelet and contourlet transforms. In: International Conference on Machine Vision and Image Processing (MVIP), pp. 65-68, Taipei, Taiwan (2012)

Luisier, F., Vonesch, C., Blu, T., Unser, M.: Fast interscale wavelet denoising of Poisson–corrupted images. Sig. Process. 90, 415–427 (2010)CrossRefMATH

Makitalo, M., Foi, A.: Optimal inversion of the generalized Anscombe transformation for Poisson-Gaussian noise. IEEE Trans. Image Process. 22(1) 91–103, (2012)

10.

Makitalo, M., Foi, A.: Optimal inversion of the Anscombe transformation in low-count Poisson Image denoising. IEEE Trans. Image Process. 20(1) 99–109, (2010)

11.

Candès, E.J., Donoho, D.L.: New tight frames of curvelets and optimal representations of objects with piecewise C² singularities. Comm. Pure Appl. Math. 57, 219–266 (2004)MathSciNetCrossRefMATH

12.

Palakkal, S., Prabhu, K.M.M.: Poisson noise removal from images using the fast discrete curvelet transform. In: National Conference on Communications (NCC), pp. 1–5, Bangalore (2011)

13.

Do, M.N., Vetterli, M.: The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans. Image Process. 14(12), 2091–2106 (2005)MathSciNetCrossRef

14.

Burt, P.J., Adelson, E.H.: The Laplacian pyramid as a compact image code. IEEE Trans. Commun. 31(4), 532–540 (1983)CrossRef

15.

Bamberger, R.H., Smith, M.J.T.: A filter bank for the directional decomposition of images: theory and design. IEEE Trans. Signal Process. 40(4), 882–893 (1992)CrossRef

16.

Blu, T., Luisier, F.: The SURE-LET approach to image denoising. IEEE Trans. Image Process. 16(11), 2778–2786 (2007)MathSciNetCrossRef

17.

Luiser, F., Blu, T., Unser, M.: Image denoising in mixed Poisson-Gaussian noise. IEEE Trans. Image Process. 20(3), 696–708 (2011)MathSciNetCrossRef

18.

Ying, L., Demanet, L., Candes, E.: 3D discrete curvelet transform. SPIE 5914, 351–361 (2005)

19.

Contourlet Toolbox: http://www.mathworks.in/matlabcentral/fileexchange/8837-contourlet-toolbox

20.

Curvelet Toolbox: http://www.curvelet.org

21.

Pure-Let Toolbox: http://www.mathworks.in/matlabcentral/fileexchange/31557-pure-let-for-poisson-image-denoising

22.

Suckling, J., Parker, J., Dance, D.R., Astley, S.M., Hutt, I., Boggis, C.R.M., Ricketts, I., Stamatakis, E., Cerneaz, N., Kok, S.L., Taylor, P., Betal, D., Savage, J.: The mammographic image analysis society digital mammogram database. In: International Workshop on Digital Mammography, pp. 211–221, York, UK (1994)

Titel: Poisson Noise Removal from Mammogram Using Poisson Unbiased Risk Estimation Technique
verfasst von: Manas Saha
Mrinal Kanti Naskar
Biswa Nath Chatterji
Verlag: Springer India
Buch: Information Systems Design and Intelligent Applications
Print ISBN: 978-81-322-2246-0

Electronic ISBN: 978-81-322-2247-7

Copyright-Jahr: 2015
DOI: https://doi.org/10.1007/978-81-322-2247-7_34

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner