Compresión de señales EEG basada en descomposición en subbandas y codificación de Golomb
Última modificación: 2011-03-26 11:40
Resumen
The need for electroencephalographic (EEG) data storage, processing and transmission for further analysis has made a great demand for efficient compression techniques. This paper presents a new compression method for EEG signals using subband descomposition and Golomb coding, enabling exploit the prevalence of low amplitude samples. Uniform scalar quantization is applied after a quality-controlled thresholding process and the elimination of dead zone. Nonzero thresholded values and runs of zeros are coded using Golomb-Rice and Golomb-Exp encoding respectively. The proposed method attains compression ratios that are better than other published results for the same reconstruction quality.