Wildemann asked . 2021-12-06

Adaptive median filter

clc;
clear all;
close all;
a=imread('cameraman.tif');
figure(1),imshow(a),title('origanal image');
b=imnoise(a,'salt & pepper',.02)
figure(2),imshow(b),title('noisy image');
Smax=9;

for i=1:254
    for j=1:254
        n=b(i:i+2,j:j+2)
        Zmin=min(n(:));
        Zmax=max(n(:));
        Zmed=median(n(:));
        sx=3;
        sy=3;

                A1=Zmed-Zmin;
                A2=Zmed-Zmax;
              if (A1>0) && (A2<0)
                  B1 = Zxy-Zmin;

                  B2 = Zxy-Zmax;
                  if (B1>0) && (B2<0)
                        b(i:i+2,j:j+2) = n(i, j);
                      break;
                  else
                       b(i:i+2,j:j+2) = Zmed;
                      break;
                  end 
              else 
                  sx=sx+2;
                  sy=sy+2;
                  if (sx > Smax) && (sy > Smax)
                      b(i:i+2,j:j+2) = n(i, j);
                  end 
                  end 
      end 
      end 

figure(3),imshow(b),title('denoised image');

? Notation
  Zmin = minimum gray level value in Sxy
  Zmax = maximum gray level value in Sxy
  Zmed = median of gray levels in Sxy
  Zxy = gray level at coordinates (x, y)
  Smax = maximum allowed size of Sxy

? Algorithm
Level A: A1 = Zmed - Zmin
          A2 = Zmed - Zmax
          if A1 > 0 AND A2 < 0, go to level B
else increase the window size
if window size < Smax, repeat level A
else output Zxy
Level B: B1 = Zxy - Zmin
B2 = Zxy - Zmax
if B1 > 0 AND B2 < 0, output Zxy
else output Zmed

adaptive median fi... , matlab , programming , signal processing