Academic Journal

Earth-Observation Image Retrieval Based on Content, Semantics, and Metadata.

Bibliographic Details
Title: Earth-Observation Image Retrieval Based on Content, Semantics, and Metadata.
Authors: Espinoza-Molina, Daniela, Datcu, Mihai
Source: IEEE Transactions on Geoscience & Remote Sensing; Nov2013, Vol. 51 Issue 11, p5145-5159, 15p
Subject Terms: Multimedia systems, Information retrieval, Information theory, Databases, Metadata
Abstract: Advances in the image retrieval (IR) field have contributed to the elaboration of tools for interactive exploration and extraction of the images from huge archives associating the content of the images with semantic meaning. This paper presents an Earth-observation (EO) IR system based on enriched metadata, semantic annotations, and image content called EO retrieval. EO retrieval generates an EO-data model by using automatic feature extraction, processing the EO product metadata, and defining semantics, which later is fully exploited for supporting complex queries. In order to demonstrate the functionality of the system, we have created a semantic catalog of TerraSAR-X as application scenario. The database is composed of 39 high-resolution TerraSAR-X scenes comprising about 50 000 image patches (160 \times 160 pixels) with their feature descriptors, 100 of metadata entries for each scene, and about 330 semantic annotations. Many query examples combining semantics, metadata, and image content for full exploitation of the image database are presented. [ABSTRACT FROM AUTHOR]
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Database: Complementary Index
Description
ISSN:01962892
DOI:10.1109/TGRS.2013.2262232