MATLAB filtering Experiment

CLC;
Clear all;
I = imread ('ight. tif ');
% %
% Use the median filter and multi-dimensional filter, and use the Rapp with the center of-4 and-8
% Las filter, Gaussian low-pass filter, Laplace filter for filtering
% %
Figure; % Figure1
Subplot (2, 2, 1 );
Imshow (I );
Title ('original image ');
J = imnoise (I, 'Salt & pepper ', 0.04); % add salt and pepper noise
Title ('prepaid and prepaid noisy ');
Subplot (2, 2 );
Imshow (j );
K = medfilt2 (J, [4, 4]) %;
Subplot (2, 2, 3 );
Imshow (k );
Title ('perform mediainfilter ');
H = ones (3, 3)/9; % multi-dimensional filtering
W = h;
G = imfilter (I, W, 'conv', 'replicate ')
Subplot (2, 2, 4 );
Imshow (g );
Title ('multidimensional filter ');
% Use the Laplace filter with center-4 and-8,
W4 = [1 1 1;
1-4 1;
1 1];
W8 = [1 1 1;
1-8 1;
1 1];
F = im2double (I );
G4 = f-imfilter (F, W4, 'replicate ');
G8 = f-imfilter (F, W8, 'replicate ');
Imshow (f );
Figure; % figure2
Subplot (1, 2 );
Imshow (G4 );
Title ('center-4 Laplace filter ');
Subplot (1, 2 );
Imshow (G8 );
Title ('center-8 Laplace filter ');
H3 = fspecial ('gaussian ', [3, 3], 0.5); % Gaussian low-pass filter
Figure; % figure3
B4 = filter2 (H3, I );
Subplot (1, 2 );
Imshow (B4, []);
Title ('gaussian low-pass filter ');
H4 = fspecial ('laplacian ', 0); % use Laplace Filter
B5 = filter2 (H4, I );
Subplot (1, 2 );
Imshow (B5, []);
Title ('laplace filter ');
% %
% Brightness change from the airspace Angle
% Change the gray level to 10-255
% %
Figure; % figure4
Subplot (2, 2, 1 );
Imshow (I );
Title ('original image ');
J2 = imadjust (I, [], [], 0.5); % enhanced low gray level
Subplot (2, 2 );
Imshow (J2 );
Title ('enhanced low grayscale level ');
J3 = imadjust (I, [], [], 2); % enhanced high gray level
Subplot (2, 2, 3 );
Imshow (J3 );
Title ('enhanced grayscale level ');
A1 = 100/255; % change the gray level to 10-255
A2 = 255/255;
A3 = 10/255;
J2 = imadjust (I, [A3, A1], [A3, a2], []);
Subplot (2, 2, 4 );
Imshow (J2 );
Title ('change the gray level to 10-255 ');
% %
% Brightness conversion from the frequency domain
% Fft2
% Because the energy is mainly concentrated in the low frequency
%. Therefore, low frequency processing can achieve the desired effect.
% %
I = imread ('ight. tif ');
Up = 0.5; % set the processing frequency limit
Down = 0.09% % set lower processing frequency limit
Figure; % figure5
Subplot (421 );
Imshow (I );
Title ('original image ');
F = double (I );
Subplot (4, 2, 3 );
Imshow (log (ABS (f), []);
Title ('unit8 converted to double ');
G = fft2 (f );
G = fftshift (g );
Subplot (4, 2, 5 );
Imshow (log (ABS (g), []);
Title ('fft2 changed image ');
[M, N] = size (g); % convert the Data Matrix
Y1 = max (ABS (G); % find the maximum frequency
Y2 = min (ABS (G); % to find the minimum frequency
Y3 = (y1-y2) * Up + y2; % sets the upper limit of Filtering
Y4 = (y1-y2) * down + y2; % sets the lower limit of Filtering
For I = 1: m
For j = 1: N
If (ABS (G (I, j) <Y4)
G (I, j) = g (I, j) ^ 1.1; % perform grayscale enhancement on the low-frequency part
End
End
End
Result = ifftshift (g );
J2 = ifft2 (result );
J3 = uint8 (ABS (J2 ));
Subplot (427 );
Imshow (J3, []);
Title ('image processed in the frequency domain ');
Subplot (422)
Imhist (I, 64 );
Subplot (424)
Imhist (F, 64 );
Subplot (426)
Imhist (G, 64 );
Subplot (428)
Imhist (J3, 64 );