Synthetic aperture radar (SAR) is a sophisticated technique of all-weather radar imaging capable of producing fine detailed images from a moving platform. When such a radar is placed on-board a satellite, compression of the raw SAR signal is necessary to reduce the large amount of collected data for downlink to a ground station within the bandwidth constraints. We present a transform-based compression system using Haar wavelet, Battle-Lemarie wavelets (linear and quadratic) and Daubechies wavelets (D-4 and D-20). The transformed data are then quantized using a bit allocation strategy. We take advantage of the multiresolution analysis to use different quantizers in each frequency band of wavelet coefficients. Since the wavelets considered here form orthonormal bases, the reconstruction is guaranteed in each case. Experimental results point out the advantages and drawbacks of this approach