SAR image compression based on piecewise linear mapping algorithm
Navneet Kumar Agrawal, K. A. Venugopalan · European Radar Conference · 2009
Block Adaptive Quantization (BAQ) algorithm is the most widely used technique for SAR Raw data and image compression but in the practical applications it encounters problem when the input data carry saturation component. According to the characteristics of the Synthetic Aperture Radar (SAR) data, the saturated component deteriorates the quantizer performance. In this paper we have devised an improved algorithm dealing with the saturated data. The experiment results show that this method does not change the compression ratio but improves the signal to noise ratio by an amount of more than 4 dB. This has been achieved by mapping the average signal magnitude with the standard deviation value of input and output signals. Based on the resultant curves it is certified that for linear part of the curve the scale factor assigned is a constant value and for non linear part a new algorithm is run giving optimum value of the threshold or the scale factor minimizing the mean square error (MSE) and maximizing the signal to noise ratio (SNR).