How & Why the Wavelets are being used in Image and Audio Processing
A wavelet is a small wave-like oscillation with an amplitude that begins at zero, increases, and then decreases back to zero. It can be thought of as a “building block” for a larger waveform, as it can be combined with other wavelets to create more complicated signals.
In mathematics and engineering, wavelets are used to analyze and represent data in a compact form. They have applications in a wide variety of fields, including image processing, audio processing, and data compression.
What is a Wavelet Transform?
A “wavelet transform” is a mathematical operation that decomposes a signal into different frequency components, represented by wavelets. It allows for the analysis of a signal at different resolutions, or scales.
The wavelet transform can be thought of as a “zoomed-in” version of the Fourier transform, which decomposes a signal into its sinusoidal frequency components. While the Fourier transform provides a global view of the frequency content of a signal, the wavelet transform can provide both local and global frequency information.
