convolution.m

This code implements the affects of linear and non linear kernel.

clear all;
close all'
clc

L=imread('Lenna.jpg');
L=rgb2gray(L);
L=im2double(L);

subplot(2,2,1), imshow(L);title('Original picture'); subplot(2,2,3), imhist(L);title('Original Histogram');
 Lnoise=imnoise(L,'gaussian'); 
subplot(2,2,2), imshow(Lnoise);title('Noisy picture'); subplot(2,2,4), imhist(Lnoise);title('Noisy Histogram');

% conv2 = Two-dimensional convolution

k1=ones(3)/9; % kernel of 3 by 3 (LPF)
LnConv=conv2(Lnoise,k1,'same');
figure(2), subplot(2,2,1), imshow(LnConv);title('Noisy picture after conv with LPF'); subplot(2,2,3), imhist(LnConv);title('Noisy Histogram after conv with LPF');

k2=ones(5)/25;% kernel of 5 by 5 (LPF)
LnConv2=conv2(Lnoise,k2,'same');
figure(3), subplot(2,2,1), imshow(LnConv2);title('Noisy picture after conv with LPF of 5 by 5'); subplot(2,2,3), imhist(LnConv2);title('Noisy Histogram after conv with LPF of 5 by 5');

k3=ones(7)/49;% kernel of 7 by 7 (LPF)
LnConv3=conv2(Lnoise,k3,'same');
subplot(2,2,2), imshow(LnConv3);title('Noisy picture after conv with LPF of 7 by 7'); subplot(2,2,4), imhist(LnConv3);title('Noisy Histogram after conv with LPF of 7 by 7');

% filter2 = Two-dimensional digital filtering

nonL1 = medfilt2(LnConv,[3 3]);
nonL2 = medfilt2(LnConv2,[3 3]);
nonL3 = medfilt2(LnConv3,[3 3]);
figure(4), subplot(2,2,1), imshow(nonL1); title('After convolution with non linear Median filter 3 by 3'); subplot(2,2,3), imhist(nonL1); title('After convolution with non linear Median filter 3 by 3');
 subplot(2,2,2), imshow(nonL2); title('After convolution with non linear Median filter 5 by 5'); subplot(2,2,4), imhist(nonL2); title('After convolution with non linear Median filter 5 by 5');
 figure(5), subplot(2,2,1), imshow(nonL3); title('After convolution with non linear Median filter 7 by 7'); subplot(2,2,3), imhist(nonL3); title('After convolution with non linear Median filter 7 by 7');