Segmentation and analysis of hyperspectral data

Author

Rotman, Stanley R. ; Silverman, Jerry ; Caefer, C.E.

Author_Institution

Air Force Res. Lab., Hanscom AFB, MA, USA

fYear

2002

fDate

1 Dec. 2002

Firstpage

123

Abstract

Summary form only given. We review a previously presented algorithm that segments hyperspectral images on the basis of the two- or three-dimensional histograms of their principal components. Some modifications to improve our previous approach are detailed. After exploring the application of morphology directly to the segmented (digital) images, we focus on the processing of our segmented images in tandem with the original hyperspectral data which produces an "anomaly gray-scale image". Such images, when subject to morphological filtering, prove to be powerful anomaly/target cueing algorithms.

Keywords

filtering theory; image segmentation; mathematical morphology; principal component analysis; spectral analysis; anomaly gray-scale image; hyperspectral data analysis; hyperspectral images; image segmentation; morphological filtering; morphology; principal components; target cueing algorithms; three-dimensional histograms; two-dimensional histograms; Data analysis; Defense industry; Digital images; Histograms; Hyperspectral imaging; Hyperspectral sensors; Image segmentation; Laboratories; Optical imaging; Spectroscopy;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Electronics Engineers in Israel, 2002. The 22nd Convention of

Print_ISBN

0-7803-7693-5

Type

conf

DOI

10.1109/EEEI.2002.1178357

Filename

1178357