SAR Image Compression with Vector Quantization of Wavelet Trees at Low Bit Rates

Author

Wang Aili ; Yang Mingji

Author_Institution

Dept. of Commun. Eng., Harbin Univ. of Sci. & Technol., Harbin, China

fYear

2009

fDate

24-26 Sept. 2009

Firstpage

1

Lastpage

4

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 0.1 dB to 1.0 dB 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.

Keywords

image coding; image reconstruction; image resolution; radar imaging; set theory; statistical analysis; synthetic aperture radar; trees (mathematics); vector quantisation; wavelet transforms; LBG algorithm; PSNR; SAR image compression; SOT; SPIHT algorithm; WVQ; codebook training; image reconstruction; low bit rate; multiresolution image analysis; perceptual quality; set partitioning-in-hierarchical-tree algorithm; spatial orientation tree structure; statistical property; synthetic aperture radar; wavelet coefficient decomposition; wavelet transform; wavelet tree; wavelet-based directional vector quantization; Algorithm design and analysis; Bit rate; Gain; Image coding; Image reconstruction; PSNR; Partitioning algorithms; Statistical analysis; Vector quantization; Wavelet coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-3692-7

Electronic_ISBN

978-1-4244-3693-4

Type

conf

DOI

10.1109/WICOM.2009.5303376

Filename

5303376