Applications of wavelet data compression using modified zerotrees in remotely sensed data

A computationally simple and effective wavelet transform based data compression algorithm has been developed at the Canadian Space Agency. It uses modified zerotrees and an optimized multi-level lookup table to improve the performance of an embedded zerotree wavelet algorithm. This new algorithm is either comparable to or surpasses previous algorithms which are much more sophisticated and computationally complex. In this paper, this algorithm was applied to compression of remotely sensed data acquired by the Airborne Visible/Infrared imaging Spectrometer (AVIRIS) and the Compact Airborne Spectrographic Imager (CASI). In order to evaluate the performance of the algorithm, the compression results obtained by this algorithm were compared with those by the LuraWave, as well as by the JPEG. The experiments show that compression ratios over 32:1 can be achieved with the fidelities greater than 40.0 dB