MATLAB Code Implementation for Wavelet Denoising

Wavelet denoising is a signal processing technique that effectively removes noise from signals by applying different types of wavelet basis functions, such as Haar and db4 wavelets. The code implementation for wavelet denoising can be achieved through specific algorithms and programming approaches. For instance, denoising code using Haar and db4 wavelet bases can demonstrate the wavelet denoising process. The implementation typically involves key steps like signal decomposition using wavelet transforms, thresholding coefficients to separate noise from meaningful signal components, and signal reconstruction using inverse wavelet transforms. Common MATLAB functions used include wavedec for decomposition, wthresh for applying thresholding rules (soft or hard thresholding), and waverec for reconstruction. By decomposing and reconstructing signals through these wavelet operations, we can effectively remove noise while preserving critical signal information. Wavelet denoising is a widely used signal processing method with extensive applications in various fields such as image processing, audio processing, and biomedical signal analysis.