Title :
Compression of raw SAR data using entropy-constrained quantization
Author_Institution :
Nat. Aerosp. Lab. NLR, Amsterdam, Netherlands
Abstract :
For the compression of raw SAR (synthetic aperture radar) data on-board spacecraft, the block adaptive quantization (BAQ) algorithm is often used due to its effectiveness and low implementation complexity. However, the entropy-constrained block adaptive quantization (ECBAQ) algorithm outperforms BAQ with respect to signal-to-quantization-noise-ratio and equals the performance of more complicated methods such as vector quantization and trellis coding variants. ECBAQ can be implemented using an architecture that is essentially not more complicated than that of a BAQ encoder and suitable for high-speed implementations. Moreover, the method features bit rate programmability with non-integer rates. This allows the SAR information throughput to be optimized for different types of applications
Keywords :
data compression; entropy codes; geophysical signal processing; geophysical techniques; image coding; quantisation (signal); radar imaging; radar signal processing; remote sensing by radar; synthetic aperture radar; terrain mapping; SAR; algorithm; bit rate programmability; block adaptive quantization; entropy-constrained block adaptive quantization; entropy-constrained quantization; geophysical measurement technique; image compression; land surface; non-integer rate; noninteger rate; radar imaging; radar remote sensing; synthetic aperture radar; terrain mapping; Bit rate; Entropy; Laboratories; NASA; Radar scattering; Space vehicles; Synthetic aperture radar; Throughput; Vector quantization; Venus;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-6359-0
DOI :
10.1109/IGARSS.2000.859673