Run-length compression of quantized Gaussian stationary signals
Oleg Seleznjev, Mykola Shykula · Random Operators and Stochastic Equations · 2012
Abstract. We consider quantization of random continuous-valued signals. In practice, analogue signals are quantized at sampling points with further compression. We study probabilistic models for run-length encoding (RLE) algorithm applied to quantized sampled random signals (Gaussian processes). This compression technique is widely used in digital signal and image processing. The mean (inverse) RLE compression ratio (or data rate savings) and its statistical inference are considered. In particular, the asymptotic normality for some estimators of this characteristic is shown. Numerical experiments for synthetic and real data are presented.