Restoration image degraded by a blurred variable in the field

• Autorzy: Bentahar Y. , Afifi M. , Dalimi H. , Amar S.

Identyfikatory

DOI

10.5277/oa180101

• Języki publikacji: EN

Abstrakty

EN

Various methods of deconvolution have been developed for several decades, notably in astronomy and microscopy. The extension of these techniques to the case of a spatially varied blur is currently an open problem. In this work, we consider a zone-invariant point spread function model to take into account blur variation in the image. Thus an algorithm has been used where the minimization of the criterion is performed in parallel on different areas of the image, while taking into account the estimates in the neighboring areas of the sub-images under consideration, so that the final solution is the minimum of the criterion where the blur is spatially varied.

Słowa kluczowe

EN

blind image deconvolution; restoration; total variation

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2018
• Tom: Vol. 48, nr 1
• Strony: 5--14
• Opis fizyczny: Bibliogr. 14 poz., rys.

Twórcy

autor

Bentahar Y.

• Laboratory, Engineering and Materials, Physics Department, Hassan II University Casablanca, Casablanca, Morocco

autor

Afifi M.

• Laboratory, Engineering and Materials, Physics Department, Hassan II University Casablanca, Casablanca, Morocco

autor

Dalimi H.

• Laboratory, Engineering and Materials, Physics Department, Hassan II University Casablanca, Casablanca, Morocco

autor

Amar S.

• Laboratory, Engineering and Materials, Physics Department, Hassan II University Casablanca, Casablanca, Morocco

Bibliografia

• [1] PAWLEY J.B., Fundamental limits in confocal microscopy, [In] Handbook of Biological Confocal Microscopy, 1972, pp. 636–641.
• [2] HYO-KYUNG SUNG, HEUNG-MOON CHOI, Nonlinear restoration of spatially varying blurred images using self-organizing neural network, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, Vol. 2, Seattle, WA, USA, 1998, pp. 1097–1100.
• [3] MEZOUARI S., HARVEY A.R., Phase pupil functions for reduction of defocus and spherical aberrations, Optics Letters 28(10), 2003, pp. 771–773.
• [4] PANKAJAKSHAN P., BO ZHANG, BLANC-FÉRAUD L., KAM Z., OLIVO-MARIN J.-C., ZERUBIA J., Blind deconvolution for thin-layered confocal imaging, Applied Optics 48(22), 2009, pp. 4437–4448.
• [5] PREZA C., CONCHELLO J.-A., Depth-variant maximum-likelihood restoration for three-dimensional fluorescence microscopy, Journal of the Optical Society of America A 21(9), 2004, pp. 1593–1601.
• [6] MAGIERA A., Point spread function in a confocal microscope with trigonometric pupil filters, Optica Applicata 30(2–3), 2000, pp. 455–461.
• [7] MAALOUF E., Contribution to fluorescence microscopy, 3D thick samples deconvolution and depth-variant PSF, PhD Thesis, Université de Haute Alsace – Mulhous, 2010.
• [8] NAGY J.G., O’LEARY D.P., Restoring images degraded by spatially variant blur, SIAM Journal on Scientific Computing 19(4), 1998, pp. 1063–1082.
• [9] HIRSCH M., SRA S., SCHÖLKOPF B., HARMELING S., Efficient filter flow for space-variant multiframe blind deconvolution, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010 pp. 607–614.
• [10] BRIERS J.D., Laser speckle contrast imaging for measuring blood flow, Optica Applicata 37(1–2), 2007, pp. 139–152.
• [11] FORNASIER M., LANGER A., SCHÖNLIEB C.-B., A convergent overlapping domain decomposition method for total variation minimization, Numerische Mathematik 116(4), 2010, pp. 645–685.
• [12] MIRAUT D., PORTILLA J., Efficient shift-variant image restoration using deformable filtering (PartI), EURASIP Journal on Advances in Signal Processing, Vol. 2012, 2012, article ID 100.
• [13] CILIEGI P., LA CAMERA A., SCHREIBER L., BELLAZZINI M., BERTERO M., BOCCACCI P., DIOLAITI E., FOPPIANI I., LOMBINI M., MASSARI D., MONTEGRIFFO P., TALIA M., Image restoration with spatially variable PSF, Proceedings of SPIE 9148, 2014, article ID 91482O.
• [14] CARLAVAN M., WEISS P., BLANC-FÉRAUD L., ZERUBIA J., Algorithme rapide pour la restauration d’image régularisée sur les coefficients d’ondelettes, GRETSI, 2009.

Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).