Analysis and modification of linear correlators for image pattern classification

Author

Chiang, Hung-Chih ; Moses, Randolph L. ; Ahalt, Stanley C.

Author_Institution

Dept. of Electr. Eng., Ohio State Univ., Columbus, OH, USA

Volume

5

fYear

1995

fDate

9-12 May 1995

Firstpage

3655

Abstract

The paper considers linear correlation filters used for image pattern recognition. First, the authors develop a statistical theory to predict the classification performance of a general class of correlation filters for wide sense stationary (WSS) clutter. This analysis includes as special cases the synthetic discriminant function (SDF), the minimum variance SDF (MVSDF), and the minimum average correlation energy (MACE) filters. Second, the authors develop a modified filter design applicable to nonzero mean noise; this latter case occurs in many applications where the magnitude image is used for classification. They compare the performance of several filters on synthetic radar imagery

Keywords

correlation methods; correlators; filtering theory; image classification; interference suppression; radar clutter; radar imaging; statistical analysis; synthetic aperture radar; classification performance; image pattern classification; image pattern recognition; linear correlation filters; linear correlators; magnitude image; minimum average correlation energy filter; minimum variance; modified filter design; nonzero mean noise; statistical theory; synthetic discriminant function; synthetic radar imagery; wide sense stationary clutter; Additive noise; Clutter; Correlators; Image analysis; Optical filters; Optical noise; Pattern analysis; Pattern classification; Synthetic aperture radar; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on

Conference_Location

Detroit, MI

ISSN

1520-6149

Print_ISBN

0-7803-2431-5

Type

conf

DOI

10.1109/ICASSP.1995.479779

Filename

479779