Wavelet Modulus Maxima Denoising

In this article, we discuss the implementation of wavelet modulus maxima denoising, an effective method for noise removal that significantly enhances signal quality. The algorithm works by identifying and preserving significant wavelet coefficient extrema while suppressing noise-related coefficients through thresholding. Our experimental validation in MATLAB demonstrates successful implementation using wavelet toolbox functions like wavedec for decomposition and waverec for reconstruction. We further explore parameter optimization strategies, including threshold selection methods (fixed threshold vs. level-dependent thresholds) and wavelet basis choices (Daubechies, Symlets, etc.) to achieve optimal denoising performance. The discussion covers practical considerations for different application scenarios, such as ECG signal processing and image denoising, where modulus maxima tracking helps preserve important signal features while removing noise. Readers will learn both the theoretical foundation and practical MATLAB implementation techniques to apply wavelet modulus maxima denoising effectively in their projects.