SAR image compression with vector quantization of wavelet trees at low bit rates

Authors:
Wang Aili;Yang Mingji
Affiliations:
Department of Communication Engineering, Harbin University of Science and Technology, Harbin, China;Department of Communication Engineering, Harbin University of Science and Technology, Harbin, China
Venue:
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Year:
2009

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Abstract

A novel wavelet-based vector quantization (WVQ) is presented for SAR image compression at low bit rates. Through analysis of the decomposed wavelet coefficients' statistic property, establish directional vectors based on spatial orientation tree (SOT) structure and apply LBG algorithm to train codebook and vector quantization of wavelet coefficients. For a typical SAR image, the reconstructed images coded by WVQ achieve gains 0.1dB to 1.0dB on average in PSNR and preserve superior perceptual quality compared with the coding results of set partitioning in hierarchical trees (SPIHT) algorithm at low bit rates.