Compresión de señales EEG basada en descomposición en subbandas y codificación de Golomb
Bazán Prieto Carlos Alberto, Blanco Velasco Manuel, Cárdenas Barrera Julián, Cruz Roldán Fernando
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.