Compression and Reconstruction of VCG Signal Based on DCT and Nearest Neighbour Interpolation

This paper presents a new technique for vectorcardiogram (VCG) signal compression based on Discrete Cosine Transform (DCT) and nearest neighbour interpolation to enhance the reconstruction quality of the signal. In the proposed method, the VCG signal is firstly preprocessed by utilizing a Savitzky Golay filter, which helps standardize the signal for further processing and reduce the influence of outliers, the signal is then applied to DCT to obtain transformed coefficients in frequency domain, after which the transformed coefficients are thresholded to increase the compression of the signal. The signal is subsequently reconstructed using the Inverse Discrete Cosine Transform (IDCT), and nearest neighbour interpolation is applied to improve the quality of the reconstructed signal. The simulation results obtained demonstrate the usefulness of the proposed technique in various performance measuring matrices such as percent root mean square difference (PRD), compression ratio (CR), peak signal to noise ratio (PSNR), signal to noise ratio (SNR), quality score (QS). The CR obtained is 35.04, PRD is 2.45, PSNR is 42.93, SNR is 35.62, QS is 15.69, similarity is 0.99788, and retained samples (RS) are 692. The experimental results indicate that the proposed method can be effectively used for VCG compression and reconstruction due to its precise diagnostic details as it provides lower PRD values at high CRs, QS, SNR, and PSNR values.