mmse_filter_cvip() - minimum mean squared error restoration filter.
new_image = mmse_filter_cvip( imageP, noise_var, kernel_size)
Input Parameters include :
- imageP - Input image can be gray image or rgb image of MxN size.
- noise_var - The variance of the noise.
- kernel_size - Block size of the filter. An odd integer between 3-11.
Output parameter include :
- new_image - The output image after filtering
This function performs the minimum mean squared error restoration filtering operation on an input image that is noise to restore it to its originla state. MMSE filter is an adaptive filter that alters its behavior based on the local statistics. The filter mitigates the noise from the image while still retaining the image details. MMSE works best with Gaussian or Uniform noise.
1. Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.
% Read image imageP = imread('noise_mmse.bmp'); % Kernel size kernel_size = 9; % Noise variance noise_var = 300; % Call function new_image = mmse_filter_cvip( imageP,noise_var,kernel_size); % Display input image figure;imshow(imageP);title('Input image'); % Display output images figure; imshow(new_image/255);title('Output image');