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Proceedings Paper

Organization and management of mass remotely sensed data for content-based retrieval
Author(s): Qimin Cheng; Guangxi Zhu
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Paper Abstract

Nowadays increasing attention has been paid to reasonable organization and effective management of vast amounts of remotely sensed data for the goal of quick browse, convenient query and Retrieval-on-Demand service. In this paper, in order to reach compromise among precision, efficiency and storage and to realize ROI coding, data partition based on Nona-tree data structure and data compression based on JPEG2000 are adopted to organize and manage original remotely sensed images. Afterwards, a prototype system in three-tier B/S mode is developed to test the validity of our data organization and management strategy for content-based retrieval mentioned above. In this system, texture-based and shape-based feature extraction algorithms based on wavelet transformation, math morphology and other relative theory are applied. Corresponding feature descriptor and similarity calculation are also given. At last, experimental results are given to show that the strategy proposed in this paper is valid, followed by brief conclusions and future directions. The work of this paper is useful to push the development of geo-spatial information services and promote content-based retrieval of remotely sensed images from experimentation to practicality.

Paper Details

Date Published: 10 November 2007
PDF: 6 pages
Proc. SPIE 6795, Second International Conference on Space Information Technology, 67952A (10 November 2007); doi: 10.1117/12.774211
Show Author Affiliations
Qimin Cheng, Huazhong Univ. of Science and Technology (China)
Guangxi Zhu, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6795:
Second International Conference on Space Information Technology

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