Wavelet Analysis Implementation Using MATLAB

Wavelet Analysis Using MATLAB

Wavelet analysis is a widely used technique for extracting features from signals and images. MATLAB provides powerful tools for implementing wavelet analysis, enabling detailed examination of features at different scales in signals and images. This method finds applications across various domains including signal processing, image analysis, and audio processing. With MATLAB, users can effectively implement wavelet analysis through functions like wavedec for wavelet decomposition, waverec for reconstruction, and wfilters for filter design.

Key MATLAB functions include:
- dwt: Discrete Wavelet Transform for single-level decomposition
- idwt: Inverse Discrete Wavelet Transform for reconstruction
- wden: Wavelet denoising with thresholding capabilities
- cwt: Continuous Wavelet Transform for time-frequency analysis
These functions support multiple wavelet families (Daubechies, Coiflets, Symlets) and allow customization of decomposition levels and threshold parameters.