We use the mathematical concept of Fast Fourier Transform to denoise an image.
Take the image as an input and with the help of Fast Fourier Transform denoise the images and respectively analyse them based on the denoising done.
The images available to us include noise. No data is without noise. The accuracy is hit when image data of signal data includes noise. In order to use the data available to us it is very essential to exclude noise in it. Fast Fourier Transforms (FFT) is a mathematical approach to de-noise the data available to us. FFT is an algorithm that computes the Discrete Fourier Transform (DFT) or Inverse Discrete Fourier Transform (IDFT) from original domain to frequency domain and do the required manipulation in order to reduce noise and try to remove noise. FFT is majorly applied for Signal processing. In this project we will attempt to de-noise images also. Wide use of FFT in signal processing is that it converts a signal into individual spectral components and provides frequency information of the signal. Basic idea of using FFT is that it transforms a function of time into a function of frequency. Thereby processing on this spectrum becomes very easy. We are using MATLAB and python programming languages to do this de-noising. We will include real time images in this project.