An Efficient High Compression Ratio Algorithm for SAR Raw Data

In this paper, the factors that affect the Block Adaptive Vector Quantization （BAVQ） compression performance are analyzed, which are the Signal to compression Noise Ratio （SNR） of Block Adaptive Quantization （BAQ）, the encoding algorithm computation complexity, the statistics and dynamic range of BAQ compressed data. Based on these factors, the paper proposes an improved BAVQ algorithm to compress Synthetic Aperture Radar （SAR） raw data. In the improved algorithm, the traditional block adaptive quantizer is replaced by more bits one. Using this improved BAVQ algorithm to compress high resolution SAR raw data, larger SNR values than the previous compression algorithms under the same compression ratio are obtained. The decompressed images reserve most of details on the images resulted from raw data.