随着合成孔径雷达（SAR）分辨率的提高，实时成像处理器单位时间内产生的图像数据越来越多，需要有效的复数图像压缩算法来降低数据存储、传输的负担。复数图像压缩算法可以在保证数据有效性的前提下减少数据量，复数图像的压缩有相位保持的特殊问题。普通光学图像的压缩方法不适用于复数图像的压缩，同时SAR图像的斑点噪声和相位的随机性也增加了压缩难度。通过考察复数图像数据的特性提出了在消除频率域冗余的基础上使用块自适应量化的SAR复数图像压缩算法。块自适应量化方法很好地适合复数图像数据动态范围大的特性，减小了量化误差。压缩前后SAR图像参数指标，如分辨率、积分旁瓣比、相位干涉效果图等表明，本文的方法可以有效地保留复数图像相位和模值信息，在一些情况下压缩比能够达到16：1。而且该算法复杂度不高，易于实时实现。

With the development of high resolution synthetic aperture radar(SAR), great quantity of complex data are generated by the real time SAR image processorwhich makes effective complex image compression algorithm necessary to release the burden of the capacity of the downlink and the storage system. Complex image compression can reduce the data amount. However the compression algorithm for the SAR complex images is specia,l which needs to keep the phase preserved. Generally speaking, the optical image compression algorithm isn’t suitable for SAR complex images. The coherent speckle noise and the random phase of SAR complex images make compression difficult. By examining the characteristic of complex image data, this paper presents an efficient compression method based on block adaptive quantization(BAQ) after removalof frequency redundancy. The BAQ is adapted to the high dynamic range ofSAR complex images and reduces the quantization error. The calibrations of SAR image such as resolution in azimuth and range, integrated side lobe ratio and peek to side lobe ratio, interference images etc. indicate that ourmethod is effective for the fidelity of SAR images’magnitude and phase under the compression ratio of 16∶1. What ismore, ithas the preference of low complexity and easy implementation in real time system.