I am working in Python, and I a trying to compute a wight matrix for a graph of pixels, and the weight of each edge is dependent on their "feature" similarity (F(i) - F(j))
, and their location similarity (X(i)-X(j))
. "Features" includes intensity, color, texture.
Right now I have it implemented and it is working, but not for color images. I at first tried to simply take some RGB values and average each pixel to convert the entire image to greyscale. But that didn't work as I had hoped, and I have read throgh a paper that suggests a different method.
They say to use this: F(i) = [v, v*s*sin(h), v*s*cos(h)](i)
where h, s, and v and the HSV color values.
I am just confused on the notation. What is this suppsed to mean? What does it mean to have three different terms separated by commas inside square brackets? I'm also confused with what the (i) at the end is supposed to mean. The solution to F(i) for any given pixel should be a single number, to be able to carry out F(i)-F(j)
?
I'm not asking for someone to do this for me I just need some clarification.