Title :
SAR image compression algorithm based on total variation decomposition
Author :
Chen-Wei Deng ; Bao-Jun Zhao
Author_Institution :
Dept. of Electron. Eng., Beijing Inst. of Technol., Beijing
Abstract :
This paper proposes a new compression framework for SAR images. A maximum a posteriori (MAP) estimator is first utilized for despeckling, and by using total variation (TV), the denoised SAR image is decomposed into structure and texture. Such two components undergo discrete wavelet transform and wavelet packet transform, respectively. And then, according to their unique characteristics, two different wavelet coding algorithms are presented to encode the respective component. Experimental results shown that the reconstructed image has good visual quality and the peak signal-to-noise ratio (PSNR) is excellent.
Keywords :
data compression; discrete wavelet transforms; image coding; image denoising; image reconstruction; image texture; maximum likelihood estimation; radar imaging; synthetic aperture radar; MAP estimation; SAR image compression algorithm; discrete wavelet transform; encoding; image decomposition; image denoising; image reconstruction; image texture; maximum a posteriori estimator; synthetic aperture radar; wavelet coding algorithm; wavelet packet transform; Discrete Wavelet Transform; Image Compression; Synthetic Aperture Radar (SAR); Total Variation;
Conference_Titel :
Radar Conference, 2009 IET International
Conference_Location :
Guilin
Print_ISBN :
978-1-84919-010-7