Data Compression Efficiency in a Modified Meyer Wavelet Filter Based on the Atomic Functions: Impact of the Filter Coefficient Count

The paper analyzes data compression efficiency of a modified Meyer wavelet filter constructed using the atomic functions. The study aims at determining an optimal number of the filter coefficients that ensure a balance between compression and the computation efficiency. A numerical experiment was carried out to evaluate data compression based on the multilevel discrete wavelet decomposition and thresholding. The analysis focuses on a number of filter coefficients influencing the compression efficiency and reconstruction accuracy. The results show that filters with more than 17 coefficients provide no significant improvement in either compression or the reconstruction quality. Comparison between the modified Meyer and Daubechies wavelet filters indicates that while both the wavelet families have similar performance in terms of data compression and reconstruction quality, they differ slightly in the sparsity effects of their detail coefficients.