Total variation based image restoration of three dimensional microscopic objects

Author

Ng, Michael K.

Author_Institution

Comput. Sci. Lab., Australian Nat. Univ., Canberra, ACT, Australia

Volume

1

fYear

1996

fDate

26-29 Nov 1996

Firstpage

288

Abstract

The inverse problem involving the determination of a three-dimensional biological structure from images obtained by means of optical-sectioning microscopy is ill-posed. Regularization methods must often be used in order to obtain a reasonable solution. Recently, the total variation (TV) regularization, as proposed by Rudin, Osher and Fatemi (1992), has become very popular for this purpose. An iterative algorithm is used for minimizing a TV-penalized least squares problems. We also employ transform based methods for solving large linear subproblems arising from TV-penalized least squares problems. Preliminary numerical results show that the method performs quite well

Keywords

conjugate gradient methods; image restoration; inverse problems; iterative methods; least squares approximations; optical microscopy; image restoration; inverse problem; iterative algorithm; large linear subproblems; numerical results; optical-sectioning microscopy; three dimensional microscopic objects; three-dimensional biological structure; total variation regularization; total variation-penalized least squares problems; transform based methods; Biology computing; Biomedical optical imaging; Fluorescence; Image restoration; Least squares approximation; Least squares methods; Optical computing; Optical microscopy; Probes; Stimulated emission;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '96. Proceedings., 1996 IEEE TENCON. Digital Signal Processing Applications

Conference_Location

Perth, WA

Print_ISBN

0-7803-3679-8

Type

conf

DOI

10.1109/TENCON.1996.608821

Filename

608821