In this paper, we describe how an evolution strategy optimizes multiresolution analysis (MRA) transforms that outperform wavelets for satellite image compression and reconstruction under conditions subject to quantization error. At three multiresolution levels and 64:1 quantization, our best evolved transform reduces mean squared error (MSE) in reconstructed images by an average of 11.71% (0.54 dB) in comparison to the 9/7 Cohen-Daubechies-Feauveau (CDF) wavelet, while continuing to match the 9/7's compression capabilities. This result establishes a new state-of-the-art for quantized digital satellite images.
['Brendan Babb', 'Frank W. Moore', 'Michael R. Peterson']
Improved multiresolution analysis transforms for satellite image compression and reconstruction using evolution strategies