Modern Applications of Wavelet Transform
Ramakrishnan, Srinivasan · IntechOpen eBooks · 2023
Types of wavelet transformsDifferent types of wavelet transforms offer diverse characteristics and functionalities, tailored for specific applications in signal processing, image analysis, data compression, and more [12, 15].Here is a list different important wavelet transforms:Continuous Wavelet Transform: The continuous wavelet transform (CWT) is a signal analysis technique.It compares a signal to modified versions of a "mother wavelet" function.The modified versions are both scaled and translated.The CWT operates constantly across different levels and durations.This allows for the examination of signals that are not consistent and have different frequency components.The characteristics of the analysis are determined by the selection of the mother wavelet.The CWT offers accurate temporal and spectral localization.This makes it suitable for signals with sudden variations or fluctuating frequencies.However, it requires significant computational resources.Discrete Wavelet Transform: The discrete wavelet transform (DWT) breaks down signals into different frequency components at multiple resolutions.It uses low-pass and high-pass filters to separate signals into approximate and detailed information.The DWT is useful for tasks like compression, noise reduction, feature extraction, and analyzing transitory occurrences in various domains.It provides a comprehensive analysis of different resolutions, collecting both high-and low-frequency data.The hierarchical representation of signals with varying levels of detail makes it applicable in many fields [10, 11].