Title :
SAR image compression using wavelet transform and soft-thresholding
Author :
Li, Y. ; Moloney, C.
Author_Institution :
Fac. of Eng. & Appl. Sci., Memorial Univ. of Newfoundland, St. John´´s, Nfld., Canada
Abstract :
Synthetic aperture radar (SAR) image compression is important in image transmission and archiving. Our studies show that the speckle noise which is inherent in SAR imaging systems is also an obstacle to image compression. In order to improve the reconstructed image quality and increase the compression efficiency, the wavelet domain soft-thresholding technique is implemented to reduce the speckle noise before compression is performed. The embedded zerotree coding algorithm is adopted to compress the de-speckled images. An 8:1 compression ratio with PSNR greater than 40 dB can be achieved for typical airborne SAR images with no significant distortion introduced by image compression
Keywords :
airborne radar; data compression; image coding; image enhancement; image reconstruction; interference suppression; noise; radar imaging; speckle; synthetic aperture radar; transform coding; wavelet transforms; PSNR; SAR image compression; SAR imaging; airborne SAR; archiving; compression efficiency; compression ratio; de-speckled images; distortion; embedded zerotree coding algorithm; image transmission; reconstructed image quality; soft-thresholding; speckle noise; synthetic aperture radar; wavelet domain soft-thresholding technique; wavelet transform; Image coding; Image communication; Image quality; Image reconstruction; PSNR; Radar polarimetry; Speckle; Synthetic aperture radar; Wavelet domain; Wavelet transforms;
Conference_Titel :
Electrical and Computer Engineering, 1997. Engineering Innovation: Voyage of Discovery. IEEE 1997 Canadian Conference on
Conference_Location :
St. Johns, Nfld.
Print_ISBN :
0-7803-3716-6
DOI :
10.1109/CCECE.1997.614870
