I have a 2 dim matrix, and I want to know e.g. all the higher values are in the upper left corner. I can't just project it into R^3 and use a standard clustering algorithm because I don't want to consider the value as a dimension by itself.
Is there an algorithm I can use for this?
To reformulate it, suppose it was like
| High values ... low values | | ... | Low values ... ... | | ... | High values .. low values |
I'd want to know that there's a "cluster" of high values in the upper left and lower left.
The matrix represents an image. The values of each cell represent the concentration of a substance at that coordinate. I want to know how homogeneous the image is (i.e. how well "mixed together" the substance is). Additionally, I would like to know where the non-homogeneity (if any) is coming from.