Performance of maximum entropy algorithms for image reconstruction from projections

Author

Dusaussoy, Nicolas J. ; Abdou, Ikram E.

Author_Institution

Dept. of Electr. Eng., Delaware Univ., Newark, DE, USA

fYear

1988

fDate

11-14 Apr 1988

Firstpage

1284

Abstract

The analysis of maximum entropy algorithms is provided for image reconstruction from projections. The performance of block- and row-type multiplicative algebraic reconstruction techniques, Bregman´s method of convex programming for entropy maximization under linear equality constraints, and MENT is compared with those of the Algebraic Reconstruction Techniques and the convolution backprojection. The quality of the successive reconstructed iterates versus the computational complexity of the algorithms is given. Furthermore, it is shown that a priori knowledge of the shape of the image to be reconstructed is easily included with these algorithms by solving a more general optimization problem

Keywords

picture processing; Bregman´s method; MENT; computational complexity; convex programming; convolution backprojection; image reconstruction; linear equality constraints; maximum entropy algorithms; multiplicative algebraic reconstruction techniques; optimization; projections; Algorithm design and analysis; Computed tomography; Convolution; Entropy; Image analysis; Image reconstruction; Iterative algorithms; Iterative methods; Shape measurement; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on

Conference_Location

New York, NY

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1988.196837

Filename

196837