you can select random images for image process

Select two images: one with strong edges of objects or features present in the images and the other with smooth edges and features. Prepare several noisy versions of the images adding Gaussian, speckle, salt-and-pepper noise (MATLAB function "imnoise" could be used for this operation). Filter the noisy images using: (i) The median filter with the following neighborhood shapes (Figure 3.14 ): 55 square and X1. (ii) The mean filter with the following neighborhood shapes (Figure 3.14 ): 33 square and 4-connected. (iii) Wiener filter. Calculate the MSE and RMS error of noisy and filtered images. Also comment the effect of blurring and noise on the Fourier spectra. Select two images: one with strong edges of objects or features present in the images and the other with smooth edges and features. Prepare several noisy versions of the images adding Gaussian, speckle, salt-and-pepper noise (MATLAB function "imnoise" could be used for this operation). Filter the noisy images using: (i) The median filter with the following neighborhood shapes (Figure 3.14 ): 55 square and X1. (ii) The mean filter with the following neighborhood shapes (Figure 3.14 ): 33 square and 4-connected. (iii) Wiener filter. Calculate the MSE and RMS error of noisy and filtered images. Also comment the effect of blurring and noise on the Fourier spectra