Using OR logical operator

I am using R2013 Matlab and trying to calculate the number of pixels which are greater than 0 and less than 255 using 5X5 window. But every time I run the code, code displays 25 when there are only 3 pixels in the image.

clc

clear all

close all

originalimage=imread('Test.jpg'); 
figure(1),imshow(originalimage);
title('Original Image');
grayimage=rgb2gray(originalimage); 
figure(2),imshow(grayimage);
title('Gray Image');
noisyimage=imnoise(grayimage,'salt & pepper',0.90);
figure(3),imshow(noisyimage);
title('Corrupted Image');
a=sum(grayimage);
% Placment of Window over image
count=0;
a=5;
b=5;
for i=1:a
    for j=1:b
        %iwn(i,j)
        if noisyimage(i,j) > 0 ||  noisyimage(i,j) < 255
            count=count+1;
        end
    end
end
fprintf('Number of non-corrupted pixels is :');
disp(count)

Please help me solving this issue.

I have attached the test image

[vidhathri bhat]

If you want pixels which are greater than 0 and less than 255, shouldn't you be using logical AND operator

[Steven Lord]

What is the class of your noisyimage variable? If it's an unsigned 8-bit integer (uint8), the elements of that variable cannot be outside the range [0, 255] as that's the allowed range of values for that data type.

Answer 1

[KSSV]

I = imread(myimage) ; 
idx = I>= 0 & I<=255 ;

Answer 2

[Peter Jarosi]

Change your OR operator to AND!

originalimage=imread('Test.jpg'); 
figure(1),imshow(originalimage);
title('Original Image');
grayimage=rgb2gray(originalimage); 
figure(2),imshow(grayimage);
title('Gray Image');
noisyimage=imnoise(grayimage,'salt & pepper',0.90);
figure(3),imshow(noisyimage);
title('Corrupted Image');
a=sum(grayimage);
% Placment of Window over image
count=0;
a=5;
b=5;
for i=1:a
    for j=1:b
        %iwn(i,j)
        if noisyimage(i,j) > 0 &&  noisyimage(i,j) < 255
            count=count+1;
        end
    end
end
fprintf('Number of non-corrupted pixels is :');
disp(count)

Consider to avoid for loops, becase the following is much faster especially for large images:

originalimage=imread('Test.jpg'); 
figure(1),imshow(originalimage);
title('Original Image');
grayimage=rgb2gray(originalimage); 
figure(2),imshow(grayimage);
title('Gray Image');
noisyimage=imnoise(grayimage,'salt & pepper',0.90);
figure(3),imshow(noisyimage);
title('Corrupted Image');
a=sum(grayimage);
% Placment of Window over image
a=5;
b=5;
idx = (noisyimage(1:a,1:b) > 0) & (noisyimage(1:a,1:b) < 255);
count = sum(sum(idx));
fprintf('Number of non-corrupted pixels is :');
disp(count)