SAR image data compression using wavelet packet transform and universal-trellis coded quantization

Abstract

A wavelet packet image coding algorithm for synthetic aperture radar (SAR) image data compression is proposed in this paper. High rate-distortion (R-D) performance of this algorithm [wavelet packet quantization universal trellis-coded quantization (WPQUTCQ)] is achieved by incorporating the wavelet packet transform for representing the rich texture information of SAR image data, the quadtree technique for classifying the wavelet packet coefficients, and the universal trellis-coded quantization (UTCQ). For a typical SAR image, WPQUTCQ outperforms set partitioning in hiearchical trees and JPEG2000 by about 1.21 and 0.81 dB in peak signal-to-noise ratio (PSNR) at 2 bpp, respectively. The effect of best basis selection on the R-D performance of coding algorithm for SAR image data compression is also evaluated through comparing the effects of different cost functions (e.g., entropy, the texture energy, which is designed for SAR image data compression particularly, and the cost function, based on the actual coding strategy proposed by us) on the R-D performance of WPQUTCQ. The experimental results show the suitability of the cost function based on the actual coding strategy for SAR image data compression when compared with other cost functions. For a typical SAR image, the coding results by WPQUTCQ corresponding to the cost function based on the actual coding strategy achieve gains 0.59 and 0.49 dB on average in PSNR when compared with the coding results corresponding to entropy and the texture energy, respectively.