Performance of different threshold function for ECG compression using Slantlet transform

In this paper, an ECG signal compression technique is presented based on Slantlet transform with different thresholding functions. The presented compression method is exploited the uniform quantization (UQ) methods with different thresholding criteria on slantlet coefficients of ECG signal. This technique the returned the better reconstruction from compressed data as compare to wavelet and discrete cosine transform technique due to better energy compaction efficiency. A detail analysis has been presented for compression and signal retrieval efficiency along with evaluation of thresholding criteria. The presented technique is tested with different ECG signal obtained from MIT-BIH arrhythmia database. The simulation and experimental results clearly illustrate the slantlet transform gives better performance in term of fidelity assessments in term of CR, SNR and PRD with better compression as compared to contemporary techniques.