Time Series processing using fft

1. What is FFT in time series?
2. How is FFT used in signal processing?
3. Why do we use FFT in image processing?

What is FFT in time series?

A fast Fourier transform (FFT) is algorithm that computes the discrete Fourier transform (DFT) of a sequence. It converts a signal from the original data, which is time for this case, to representation in the frequency domain.

How is FFT used in signal processing?

The FFT algorithm is used to convert a digital signal (x) with length (N) from the time domain into a signal in the frequency domain (X), since the amplitude of vibration is recorded on the basis of its evolution versus the frequency at that the signal appears [40].

Why do we use FFT in image processing?

The Fast Fourier Transform (FFT) is commonly used to transform an image between the spatial and frequency domain. Unlike other domains such as Hough and Radon, the FFT method preserves all original data. Plus, FFT fully transforms images into the frequency domain, unlike time-frequency or wavelet transforms.