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Blind restoration of images degraded with mixed poisson-Gaussian noise with application in transmission electron microscopy
Faculty of Technical Sciences, University of Novi Sad, Serbia.
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia. (Centre for Image Analysis)ORCID-id: 0000-0001-7312-8222
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Bildanalys och människa-datorinteraktion. Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Matematisk-datavetenskapliga sektionen, Institutionen för informationsteknologi, Avdelningen för visuell information och interaktion. Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia. (Centre for Image Analysis)
2016 (engelsk)Inngår i: 2016 Ieee 13Th International Symposium On Biomedical Imaging (ISBI), IEEE, 2016, s. 123-127Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Noise and blur, present in images after acquisition, negatively affect their further analysis. For image enhancement when the Point Spread Function (PSF) is unknown, blind deblurring is suitable, where both the PSF and the original image are simultaneously reconstructed. In many realistic imaging conditions, noise is modelled as a mixture of Poisson (signal-dependent) and Gaussian (signal independent) noise. In this paper we propose a blind deconvolution method for images degraded by such mixed noise. The method is based on regularized energy minimization. We evaluate its performance on synthetic images, for different blur kernels and different levels of noise, and compare with non-blind restoration. We illustrate the performance of the method on Transmission Electron Microscopy images of cilia, used in clinical practice for diagnosis of a particular type of genetic disorders.

sted, utgiver, år, opplag, sider
IEEE, 2016. s. 123-127
Serie
IEEE International Symposium on Biomedical Imaging, ISSN 1945-7928
Emneord [en]
Image restoration, Minimization, Estimation, Transmission electron microscopy, Noise measurement, PSNR, Total variation
HSV kategori
Forskningsprogram
Datoriserad bildbehandling; Datoriserad bildanalys
Identifikatorer
URN: urn:nbn:se:uu:diva-308086DOI: 10.1109/ISBI.2016.7493226ISI: 000386377400030ISBN: 9781479923496 (tryckt)ISBN: 9781479923502 (tryckt)OAI: oai:DiVA.org:uu-308086DiVA, id: diva2:1049176
Konferanse
IEEE 13th International Symposium on Biomedical Imaging (ISBI), 2016
Tilgjengelig fra: 2016-11-23 Laget: 2016-11-23 Sist oppdatert: 2018-11-28

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