Wavelet-based compression of SAR raw data

Enrico Magli, Gabriella Olmo, Barbara Penna

Abstract: In this paper we compare two compression methods for SAR raw data, based on the discrete wavelet transform (DWT). In the former, the data are subject to blockwise normalization prior to being transformed by means of the DWT processor; then, an optimal rate allocation is performed for each subband. The latter employs the well known JPEG 2000 to perform the DWT and the subsequent quantization, rate allocation and coding steps; both the cases of normalized and non normalized data are considered. The performance of the algorithms have been tested on SIR-C/X-SAR data, and FBAQ is employed as the term of comparison for both quality and compression ratio. The obtained results show that the if the samples are normalized, the performance of the DWT-based algorithms is more predictable, and less subject to statistical fluctuations related to the characteristics of the input data.