Simultaneous noise reduction and SAR image data compression using best wavelet packet basis

Abstract

We propose a novel method for simultaneous noise reduction and data compression based on shrinking, quantizing and coding the wavelet packet (WP) coefficients. A dynamic programming and fast pruning algorithm is used to efficiently choose the best basis from the entire library of admissible WP bases, and jointly optimize the bit allocation strategy and the quantization scheme in the rate-distortion framework. Soft-thresholding in the wavelet domain can significantly suppress noise, e.g., the speckles of the synthetic aperture radar images, while maintaining bright reflections for subsequent detection and recognition. Optimal bit allocation, quantization and entropy coding achieve the goal of compression while maintaining the fidelity of the image.