Can you please tell Mat lab code for Progressive switching median filter?

Answer 1

PSMF(x)

%% Implementation of Progressive Switching Median Filter

%% Base Paper : Zhou Wang and David Zhang, "Progressive Switching Median

%% Filter for the Removal of Impulse Noise from Highly Corrupted Images",

%% IEEE Trans. on Cir. and Sys., vol. 46, no. 1, Jan. 1999.

%% Function Y = PSMF(x)

%% input x = Image is corrupted by Salt & Pepper Noise

%%

%% Example: Y = PSMF(x);

%% Posted date : 16 - 10 - 2008

%% Modified date :

%%

%% Developed By : K.Kannan (kannan.keizer@gmail.com)

%% & Jeny Rajan (jenyrajan@gmail.com)

%% Medical Imaging Research Group (MIRG), NeST,

%% Trivandrum.

%% Progressive Switching Median Filter

function Y = PSMF(x)

x = double(x);

WF = 3; ND = 3;T = 40;a = 65;b = -50;

M = medfilt2(x,[3 3]);

N = abs(x - M);

N(N>T)=0;

N = N ~= 0;

N = double(N);

R = sum(N(:))/(size(x,1) * size(x,2));

if R <= 0.25

WD = 3;

else

WD = 5;

end

TD = a + (b * R);

z = IMPDET(x,ND,WD,TD);

Y = NF(x,z,WF);

%% Impulse Detection

function F1 = IMPDET(x,ND,WD,TD)

X = x;

M = medfilt2(X,[WD WD]);

D = abs(X - M);

F = zeros(size(x));

F(D>=TD)=1;

F1 = F;

X(F1==F)=X(F1==F);

X(F1~=F)=M(F1~=F);

for i = 1:ND-1

M = medfilt2(X,[WD WD]);

F1(abs(X - M)<TD)=F(abs(X - M)<TD);

F1((X - M)>=TD)=1;

X(F1==F)=X(F1==F);

X(F1~=F)=M(F1~=F);

F = F1;

end

return;

%% Noise Filtering

function Y = NF(x,f,WF)

g = f;

Y = x;

Y1 = Y;

g1 = g;

s = sum(g(:));

while s ~= 0

M = medfilt2(Y,[WF WF]);

Y1(g==1)=M(g==1);

g1(Y~=Y1)=0;

Y = Y1;

g = g1;

s1 = sum(g(:));

if s1 ~= s

s = s1;

else

s = 0;

end

end

return;