Adaptive Vector Quantization of SAR Raw Data

This paper deals with the compression algorithms of synthetic aperture radar (SAR) raw data based on vector quantization (VQ) techniques. The block adaptive tree-structured vector quantization (BATSVQ) algorithm and the block adaptive lattice vector quantization (BALVQ) algorithm are presented. Compared with the block adaptive vector quantization (BAVQ) algorithm, both of the proposed methods using constrained vector quantizer take the full advantage of SAR raw data properties of a Gaussian stationary process after a blockwise normalization. Live SAR data implementations and quantitative analysis of resultant images show that, a better trade-off between performance and complexity can be achieved by using the BATSVQ and BALVQ algorithms.