Question

I am trying to implement Laplacian , this is my kernel:

0  1  0 
1 -4  1
0  1  0

I am showing only relevant code, i have an 3×3 array Pixel which stores the neighbouring Pixel values

Pixel[i][j].val[k] signifies RBG values for k=0,1,2 respectively.

long double kernel[3][3],mean=0,nTemp=0,c,sum=0,n=0,s=0,d=0;

for ( row = 1; row < rows - 2; row++ )
    {
        for ( col = 1; col < cols - 2; col++ )
        {
            nTemp = 0.0;
            for (i=0 ; i < 3; i++)
            {
                for (j=0 ; j < 3; j++)
                {
                        c = (Pixel[i][j].val[0]+Pixel[i][j].val[1]+Pixel[i][j].val[2])/3;
                        nTemp += (double)c * kernel[i][j];
                }
            }

            sum += nTemp;
            n++;
        }
    }


for ( row = 1; row < rows - 2; row++ )
    {
        for ( col = 1; col < cols - 2; col++ )
        {
            nTemp = 0.0;

            for (i=0 ; i < 3; i++)
            {
                for (j=0 ; j < 3; j++)
                {
                        c = (Pixel[i][j].val[0]+Pixel[i][j].val[1]+Pixel[i][j].val[2])/3;

                        nTemp += (double)c * kernel[i][j];
                }
            }

            s = (mean - nTemp);
            d += (s * s);
        }
    }
// PROBLEM IS HERE SIGMA (s) and Deviation (d) are always 0, 

I get a completely Blackened image, please tell me where am i going wrong?

Answer 1

You’re only ever using Pixel[i][j] for 0 <= i, j < 3, shouldn’t that be Pixel[row+i][col+j] in the inner loops?