Model-based reconstruction of multiple circular and elliptical objects from a limited number of projections

Author

Wang, S. ; Liu, B. ; Kulkarni, S.R.

Author_Institution

Dept. of Electr. Eng., Princeton Univ., NJ, USA

Volume

5

Issue

9

fYear

1996

fDate

9/1/1996 12:00:00 AM

Firstpage

1386

Lastpage

1390

Abstract

We consider tomographic image reconstruction from a limited number of noisy projections. An efficient algorithm based on maximum likelihood estimation (MLE) is developed to reconstruct images of multiple discs with unknown locations and radii. The algorithm is successfully applied to images with signal-to-noise ratio (SNR) as low as 0 dB, using as few as 16 projections, and containing as many as twelve discs with widely varying radii. Experimental results show that our approach significantly outperforms conventional convolution back projection. The algorithm is successfully extended to the multiple ellipse case

Keywords

image reconstruction; maximum likelihood estimation; object detection; tomography; MLE; limited number of projections; maximum likelihood estimation; multiple circular objects; multiple discs; multiple elliptical objects; noisy projections; signal-to-noise ratio; tomographic image reconstruction; Computational complexity; Convolution; Gaussian noise; Image reconstruction; Maximum likelihood detection; Maximum likelihood estimation; Noise level; Signal to noise ratio; Tomography; Two dimensional displays;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.535853

Filename

535853