Compression of Satellite Imagery Sequences Using Wavelet for Detection of Natural Disaster

Santoso, Albertus Joko and Dewi, Findra Kartika Sari and Sidhi, Thomas Adi Purnomo (2014) Compression of Satellite Imagery Sequences Using Wavelet for Detection of Natural Disaster. International Journal of Advanced Science and Technology (IJAST), 62. pp. 55-64. ISSN 2005-4238

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Text (Albertus Joko Santoso, Findra Kartika Sari Dewi and Thomas Adi Purnomo Sidhi) 12. Compression of Satellite Imagery Sequences.pdf Download (618kB) | Preview

Abstract

Indonesia, geographically and geologically, is potentially encounter natural disasters. One of the tools used to early detect disaster is sensor of ocean waves change, but it has drawbacks including the time difference between information/warnings obtained with the disaster event is very short, less than 30 minutes. The faster detector is required, so the time difference will be longer. For example, early detection of natural disasters information system, which can be made with the pattern recognition of satellite imagery sequences of before and during natural disaster images. This study was conducted to determine the right wavelet to compress the satellite image sequences. The compressed images will be used to perform the pattern recognition of natural disaster using artificial neural network. This study use satellite imagery sequences of tornadoes and hurricanes. The eight wavelets used are Haar, Coiflet 1, Coiflet 3, Symlet 2, Symlet 5, 1 AJS, AJS 2, and AJS 3. The test results are then compared with the compression ratio. Result of this study are the comparison of wavelet used to compress satellite imagery sequences, which is save the storage space, access time, processing time and delivery time.

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