A subspace decomposition method for point source localization in blurred images

Author

Gunsay, Metin ; Jeffs, Brian D.

Author_Institution

Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA

fYear

1994

fDate

19-22 Apr 1994

Abstract

We address the problem of resolving blurred point sources in intensity images. A new approach to image restoration is introduced which is a 2-D generalization of techniques originating from the field of direction of arrival estimation (DOA). In the 2-D frequency domain, algorithms, such as MUSIC, may be adapted to search for these point sources. A generalization of array smoothing based on a regularization operator is introduced for 2-D arrays in order to achieve rank enhancement in the signal space of the covariance matrix

Keywords

astronomy; astronomy computing; covariance matrices; direction-of-arrival estimation; frequency-domain analysis; image restoration; smoothing methods; 2D arrays; 2D frequency domain; MUSIC algorithm; algorithms; array smoothing; astronomy; blurred images; covariance matrix; direction of arrival estimation; image restoration; intensity images; point source localization; rank enhancement; regularization operator; subspace decomposition method; synthetic star cluster; Additive noise; Biomedical imaging; Convolution; Direction of arrival estimation; Frequency domain analysis; Image resolution; Image restoration; Multiple signal classification; Signal resolution; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on

Conference_Location

Adelaide, SA

ISSN

1520-6149

Print_ISBN

0-7803-1775-0

Type

conf

DOI

10.1109/ICASSP.1994.389386

Filename

389386