Understanding Discrete Wavelet Transform (DWT) for Signal and Image Processing

DWT stands for Discrete Wavelet Transform. It is a mathematical technique used to transform a signal or image into a frequency domain representation using wavelets.

Wavelets are small, smooth, and compact functions that are used to represent a signal or image at multiple scales and resolutions. The DWT decomposes a signal or image into different components, each of which represents a different frequency range. This allows for more efficient and effective compression and analysis of signals and images.

The DWT is commonly used in many fields, including signal processing, image processing, data compression, and feature extraction. It has applications in areas such as audio compression, image compression, and biomedical signal processing.