Categorization based Relevance Feedback Search Engine for Earth Observation Images Repositories

Author

Costache, Mihai ; Maitre, Henri ; Datcu, Mihai

Author_Institution

Telecom Paris, GET, Paris

fYear

2006

fDate

July 31 2006-Aug. 4 2006

Firstpage

13

Lastpage

16

Abstract

Presently Earth observation (EO) satellites acquire huge volumes of high resolution images very much over-passing the capacity of the users to access the information content of the acquired data. Thus, in addition to the existing methods for EO data and information extraction, new methods and tools are needed to explore and help to discover the information hidden in large EO image repositories. This article presents a categorisation based Relevance Feedback (RF) search engine for EO images repositories The developed method is presented as well results obtained for a SPOT5 satellite image database.

Keywords

geophysical techniques; geophysics computing; relevance feedback; remote sensing; search engines; very large databases; visual databases; EO data extraction; Earth observation images repositories; SPOT5 satellite image database; categorization based relevance feedback search engine; high resolution images; large EO image repositories; remote sensing images; Earth; Feedback; Filters; Image databases; Image retrieval; Radio frequency; Satellites; Search engines; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2006. IGARSS 2006. IEEE International Conference on

Conference_Location

Denver, CO

Print_ISBN

0-7803-9510-7

Type

conf

DOI

10.1109/IGARSS.2006.8

Filename

4241155