SAR image compression

Abstract

Classical image compression algorithms such as Discrete Cosine Transform (DCT) [1], Karhunen-Loeve Transform (KLT) [1], and Subband Decomposition using Wavelet Filters (SDWF) [2,3] are well-understood for optical imaging. However, their applications to synthetic aperture radar (SAR) images have not been well-studied. This paper applies DCT, KLT and SDWF to raw SAR images after appropriate preprocessing, and compares the results based on three performance criteria, namely energy gain (E-C), transform coding gain (G(T)), and peak-to-peak signal-to-noise ratio (PSNR).