Progressive search and retrieval in large image archives
IBM Journal of Research and Development - Papers on mustimedia systems
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
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As various sensors with different spatial resolutions, spectral resolutions, etc., have been in operation, an extremely large image database is ready. How to retrieve the relevant information is a critical problem in the context of quick damage assessment. This study develops a framework to integrate medium resolution (Landsat or ASTER) and high-resolution (QuickBird or IKONOS) satellite images and digital elevation data in mapping tsunami-affected areas. The processing flows upwards from macro-scale (medium spatial resolution data) to micro-scale (high spatial resolution data). Across this pyramidal searching, only necessary data is acquired, processed and the focused geographical extent is narrowed. Suitable pixel-based and object-based processing methods are also developed. Using the developed processing flow drastically reduces acquisition cost and processing time. The selected test sites in Phangnga and Phuket Provinces, Thailand, which were severely affected by the 2004 Indian Ocean tsunami, are used to demonstrate the performance of the framework. Further studies include the implementation of the processing system and the extension of the idea to other natural hazards.