noisy image

In digital image processing, we can use several filtering operations for finding objects, edges and feature points. In this laboratory work, you will implement spatial domain and frequency domain filtering processes. Laboratory work can be performed by using MATLAB and its predefined functions. 1) Use digital image 2) Generate the kernel which is given below. Then, convolve it with the downloaded image. 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9 1/9 Display the image and discuss the result. 3) Generate the kernel which is given below. Then, convolve it with the downloaded image. 0 -1 0 -1 4 -1 -1 0 Display the image and discuss the result 4) Take Fourier transform of the image by using function fft2(). Then, display its magnitude and phase responses. 5) Magnitude response of Fourier transform can be too dark and gray level variations may not be visible. Hence, pass it through non-linear function which provides better visibility in the magnitude response. You should determine a non-linear function and then, display the calculated new magnitude response. 6) Generate a lowpass filter (whose shape should be circle - circular symmetric - ). Multiply it with the Fourier transform response of the image. Be careful about the Forier transform function. It is defined from 0 to N-1 (in terms of index numbers it is from 1 to N). DC frequency is assigned to (0,0) and highest frequency is at (N/2, N/2). Take inverse Fourier transform and display the result. Discuss the obtained result. 7) Generate a highpass filter (inverse of the filter given in (6)). Multiply it with the Fourier transform response of the image. Be careful about the Forier transform function. It is defined from 0 to N-1 (in terms of index numbers it is from 1 to N). DC frequency is assigned to (0,0) and highest frequency is at (N/2, N/2). Take inverse Fourier transform and display the result. Discuss the result