CCSDS-IDC(consultative committee for space data systems-image data compression)

which has been proposed as a space remote image data compression standard by NASA

is suitable for synthetic aperture radar(SAR) amplitude image and other remote sensing image compression. It uses discrete wavelet transform(DWT)

and performs hierarchical DWT coefficients encoding from large scales to small scales in the bit plane encoding. When the energy of DWT coefficients mainly concentrates on the large scale(low frequency) and there is energy attenuation from largescale to small scale

CCSDS-IDC can achieve high compression efficiency. Unlike optical images

SAR image data is always complex-valued

which has a wide range of use. For example

interferometric SAR can use the phase difference of two complex SAR images to obtain elevation information and has been widely applied in environmental monitoring

mapping

and other fields. However

vast amounts of complex SAR image data require transmission and storage resources

which raise the needs for efficient SAR complex image data compression. In this paper

we study the performance of CCSDS-IDC for complex SAR image data and identify that CCSDS-IDC suffers from low efficiency for complex SAR image data coding. As the real part and imaginary part of SAR complex image data have many high-frequency oscillation components

the large-amplitude significant DWT coefficients mainly concentrate on a small scale and the DWT coefficients do not exhibit attenuation from large scale to small scale. Due to this

CCSDS-IDC has to spend a large amount of bits on coding the significant DWT coefficients on a small scale for the complex SAR image data

which degrades the rate distortion performance of CCSDS-IDC. Considering the clustering characteristics of DWT coefficients corresponding to the spatial structure of the SAR complex image data

we propose Quadtree Coding(QC) based on DWT for complex SAR image data compression

and find that QC achieves high performance for complex SAR image data. Compared with CCSDS-IDC based on DWT

QC based on DWT can improve the amplitude peak-signal-to-noise-ratio(PSNR) up to 4.4 dB and reduce the MPE up to 0.368 at the same bitrate. Though the directional lifting wavelet transform(DLWT) can aggregate the energy of wavelet coefficients to low frequency and improve the performance of CCSDS-IDC

the QC based on DWT still outperform the CCSDS-IDC based on DLWT for complex SAR image data compression. Compared with CCSDS-IDC based on DLWT

the QC based on DWT can improve the amplitude PSNR up to 3.08 dB and reduce the MPE 0.25. For other images

such as SAR amplitude images and optical images

which exhibit different DWT coefficients properties from that of complex SAR image data

QC based on DWT also achieves nice compression performance. CCSDS-IDC has a poor performance for complex SAR image data

however

the QC is more suitable for complex SAR image data coding. For designing image coding algorithm based on DWT

compared with using the attenuation property

exploiting the clustering property may be the first choice to code more kinds of images efficiently. This is because clustering characteristic being related to the image geometrical structures always exist while attenuation characteristic being related to some smooth constrains may lack for some kinds of images.