Organization and management of mass remotely sensed data for content-based retrieval

Qimin Cheng; Guangxi Zhu

doi:10.1117/12.774211

10 November 2007 Organization and management of mass remotely sensed data for content-based retrieval

Qimin Cheng, Guangxi Zhu

Proceedings Volume 6795, Second International Conference on Space Information Technology; 67952A (2007) https://doi.org/10.1117/12.774211
Event: Second International Conference on Spatial Information Technology, 2007, Wuhan, China

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.

Citation Download Citation

Qimin Cheng and Guangxi Zhu "Organization and management of mass remotely sensed data for content-based retrieval", Proc. SPIE 6795, Second International Conference on Space Information Technology, 67952A (10 November 2007); https://doi.org/10.1117/12.774211

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