With the development of high-resolution SAR systems

it is necessary to develop image compression techniques to compress these products because the volume of data in SAR systems is increasing rapidly.Unlike the compression of SAR real images

the compression of SAR complex images usually needs to keep the phase information which is a difficulty task.In this paper

the correlation of complex SAR images data before and after the wavelet transform is analyzed.Then the theory and methodology of a wavelet-based compressing method for SAR complex images

the Wavelet Transform Block Adaptive Vector Quantization（WT-BAVQ） algorithm

is presented.At the same time

as the compression is performed to a SAR complex image with WT-BAVQ

the Average Spatial Correlation（ASC） and Average Phase Correlation Coefficient（APCC） are achieved and the decompressed image is given.Moreover

the comparison of ASC and APCC is made with Block Adaptive Vector Quantization（BAVQ）

Wavelet Transform Vector Quantization（WT-VQ） and wavelet transform block adaptive quantization （WT-BAQ）.The experiments manifest that with the same compression ratio

the ASC of WT-BAVQ is higher than that of the other three algorithms.