Fast retrieval of multi- and hyperspectral images using relevance feedback

Author

Alber, Irwin E. ; Xiong, Ziyou ; Yeager, Nancy ; Farber, Morton ; Pottenger, William M.

Author_Institution

Boeing Integrated Defense Syst., Seal Beach, CA, USA

Volume

3

fYear

2001

fDate

2001

Firstpage

1149

Abstract

A high speed of retrieval is very important to developing an effective image cube search algorithm for the remote sensing community. Following the work of Berman and Shapiro (1999), it is shown that a triangle inequality search technique applied to a relevance feedback retrieval algorithm can significantly speed up the search for and retrieval of physical events of interest in large remote-sensing databases. An improvement in retrieval speed is illustrated using hurricane queries applied to the multispectral GOES database

Keywords

content-based retrieval; geophysics computing; image retrieval; relevance feedback; remote sensing; search problems; storms; visual databases; hurricane queries; hyperspectral images; image cube search algorithm; multispectral GOES database; multispectral images; relevance feedback; relevance feedback retrieval algorithm; remote sensing; triangle inequality search technique; Algorithm design and analysis; Feedback; Hurricanes; Hyperspectral imaging; Image analysis; Image databases; Image retrieval; Information retrieval; Radio frequency; Remote sensing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2001. IGARSS '01. IEEE 2001 International

Conference_Location

Sydney, NSW

Print_ISBN

0-7803-7031-7

Type

conf

DOI

10.1109/IGARSS.2001.976774

Filename

976774