In this paper, we introduce a progressive SAR image compression based on bandlet transform (BT) and a modified Embedded Zero-Block Coding (EZBC) algorithm. BT as a new developed adaptive multi-resolution geometry analysis tool exhibits enormous potential in compression based on geometric regularity. Since in SAR images, important information is spread in the entire frequency spectrum, discrete wavelet transform (DWT) cannot provide optimal representation and instead BT is employed to provide a sparse representation of the image. A modified version of EZBC algorithm is introduced to efficiently encode the bandlet coefficient in a progressive manner in which fidelity of the reconstructed image in the decoder gradually improves as more bits are received and decoded. Numerical tests show that our method provide a significant improvement particularly for low bit rate SAR image compression.
kuchakzadeh, M., Danyali, H., & Samadi, S. (2014). Progressive SAR Image Compression Using Low Complexity Bandlet Transform and Modified EZBC. Journal Of Electrical Systems And Signals, 2(1), 9-14. doi: 10.22067/ess.v2i1.42320
MLA
maryam kuchakzadeh; Habibolah Danyali; Sadegh Samadi. "Progressive SAR Image Compression Using Low Complexity Bandlet Transform and Modified EZBC", Journal Of Electrical Systems And Signals, 2, 1, 2014, 9-14. doi: 10.22067/ess.v2i1.42320
HARVARD
kuchakzadeh, M., Danyali, H., Samadi, S. (2014). 'Progressive SAR Image Compression Using Low Complexity Bandlet Transform and Modified EZBC', Journal Of Electrical Systems And Signals, 2(1), pp. 9-14. doi: 10.22067/ess.v2i1.42320
VANCOUVER
kuchakzadeh, M., Danyali, H., Samadi, S. Progressive SAR Image Compression Using Low Complexity Bandlet Transform and Modified EZBC. Journal Of Electrical Systems And Signals, 2014; 2(1): 9-14. doi: 10.22067/ess.v2i1.42320
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