TY - GEN
T1 - SAR image compression algorithm based on total variation decomposition
AU - Deng, Chen Wei
AU - Zhao, Bao Jun
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Discrete Wavelet Transform
KW - Image Compression
KW - Synthetic Aperture Radar (SAR)
KW - Total Variation
UR - http://www.scopus.com/inward/record.url?scp=70350147191&partnerID=8YFLogxK
U2 - 10.1049/cp.2009.0452
DO - 10.1049/cp.2009.0452
M3 - Conference contribution
AN - SCOPUS:70350147191
SN - 9781849190107
T3 - IET Conference Publications
BT - IET International Radar Conference 2009
T2 - IET International Radar Conference 2009
Y2 - 20 April 2009 through 22 April 2009
ER -