Investigation of wavelets for raw SAR data compression
A. El-Boustani, K. Brunham, Witold Kinsner · 2004
Synthetic aperture radar (SAR) is a sophisticated remote sensing tool that is capable of providing high resolution images from a moving platform. Due to the very poor correlation and high entropy of SAR raw data, redundancy reduction techniques have not proven successful and a lossy compression is necessary. In this paper, we present a compression of the raw SAR signal using wavelets. We first determine the best performing 1-D wavelet basis experimentally. Since the experiments show that no standard wavelet basis outperforms BAQ, we propose to determine an optimal 2-D wavelet which is learned directly from the raw SAR data. The optimality criterion in the learning processes is redundancy minimization in the transform domain. Experiments show that this optimal wavelet performs better than the standard wavelets.