Incorrect result of image subtraction

Question

I wanted to subtract two images pixel by pixel to check how much they are similar. Images have the same size one is little darker and beside brightness they don\'t differ. B

Answer 1

You did not "subtract one pixel from the other" correctly. getRGB returns "an integer pixel in the default RGB color model (TYPE_INT_ARGB)". What you are seeing is an "overflow" from one byte into the next, and thus from one color into the next.

Suppose you have colors 804020 - 404120 -- this is 3FFF00; the difference in the G component, 1 gets output as FF.

The correct procedure is to split the return value from getRGB into separate red, green, and blue, subtract each one, make sure they fit into unsigned bytes again (I guess your Math.abs is okay) and then write out a reconstructed new RGB value.

Answer 2

I found this which does what you want. It does seem to do the same thing and it may be more "correct" than your code. I assume it's possible to extract the source code.

http://tutorial.simplecv.org/en/latest/examples/image-math.html

/Fredrik Wahlgren

Answer 3

The problem here is that you can't subtract the colors direcly. Each pixel is represented by one int value. This int value consists of 4 bytes. These 4 bytes represent the color components ARGB, where

A = Alpha
R = Red
G = Green
B = Blue

(Alpha is the opacity of the pixel, and always 255 (that is, the maximum value) in BMP images).

Thus, one pixel may be represented by

(255, 0, 254, 0)

When you subtract another pixel from this one, like (255, 0, 255, 0), then the third byte will underflow: It would become -1. But since this is part of ONE integer, the resulting color will be something like

(255, 0, 254, 0) - 
(255, 0, 255, 0) = 
(255, 255, 255, 0)

and thus, be far from what you would expect in this case.

---

The key point is that you have to split your color into the A,R,G and B components, and perform the computation on these components. In the most general form, it may be implemented like this:

int argb0 = image0.getRGB(x, y);
int argb1 = image1.getRGB(x, y);

int a0 = (argb0 >> 24) & 0xFF;
int r0 = (argb0 >> 16) & 0xFF;
int g0 = (argb0 >>  8) & 0xFF;
int b0 = (argb0      ) & 0xFF;

int a1 = (argb1 >> 24) & 0xFF;
int r1 = (argb1 >> 16) & 0xFF;
int g1 = (argb1 >>  8) & 0xFF;
int b1 = (argb1      ) & 0xFF;

int aDiff = Math.abs(a1 - a0);
int rDiff = Math.abs(r1 - r0);
int gDiff = Math.abs(g1 - g0);
int bDiff = Math.abs(b1 - b0);

int diff = 
    (aDiff << 24) | (rDiff << 16) | (gDiff << 8) | bDiff;
result.setRGB(x, y, diff);

Since these are grayscale images, the computations done here are somewhat redundant: For grayscale images, the R, G and B components are always equal. And since the opacity is always 255, it does not have to be treated explicitly here. So for your particular case, it should be sufficient to simplify this to

int argb0 = image0.getRGB(x, y);
int argb1 = image1.getRGB(x, y);

// Here the 'b' stands for 'blue' as well
// as for 'brightness' :-)
int b0 = argb0 & 0xFF;
int b1 = argb1 & 0xFF;
int bDiff = Math.abs(b1 - b0);

int diff = 
    (255 << 24) | (bDiff << 16) | (bDiff << 8) | bDiff;
result.setRGB(x, y, diff);