On classification of multispectral infrared image data

Author

Cheung, Julian ; Ferris, David ; Kurz, Ludwik

Author_Institution

Dept. of Electr. Eng., New York Inst. of Technol., NY, USA

Volume

6

Issue

10

fYear

1997

fDate

10/1/1997 12:00:00 AM

Firstpage

1456

Lastpage

1460

Abstract

A detector is proposed that is based on a model in which the signal components consist of radiant thermal energy from either the small target or the intense, highly structured background. The resulting statistic is effective in enhancing the target and suppressing cluttered background. Estimation of the system parameters based on stochastic approximation techniques is presented. Simulation results demonstrate the practicality of the proposed detector

Keywords

Gaussian distribution; approximation theory; clutter; image classification; infrared imaging; infrared spectra; iterative methods; parameter estimation; spectral analysis; stochastic processes; Gaussian distribution; IR detector; cluttered background suppression; iterative stochastic techniques; multispectral infrared image data classification; optimal likelihood ratio detector; radiance statistics; radiant energy; radiant thermal energy; sensor nois; signal components; simulation results; small target; statistic; stochastic approximation techniques; structured background; system parameter estimation; Infrared detectors; Infrared image sensors; Infrared imaging; Optical imaging; Remote monitoring; Sensor phenomena and characterization; Spatial resolution; Statistics; Stochastic systems; Temperature sensors;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.624975

Filename

624975