A Compression Algorithm for SAR Raw Data Based on the Combination of Discrete Cosine Transform and Block-Adaptive Quantization
基于DCT的分块自适应量化算法及其用于SAR原始数据压缩

In this paper, an algorithm for compressing synthetic aperture radar raw data is proposed. This algorithm is based on the combination of discrete cosine transform and block-adaptive quantization. The known results that a block normalized SAR raw signal is a Gaussian stationary process are exploited in order to re-array the DCT coefficients. Coupled with a proper bit allocation strategy and block-adaptive quantization on re-arrayed coefficients matrix, this algorithm exhibits notably an interesting performance/complexity trade-off with respect to conventional methods such as BAQ. Simulation results on real-world SAR raw data also show that the proposed algorithm outperforms methods based on wavelets as to SNR and PSNR.