Say I have two heatmaps: Each pixel of the heatmap represents a certain probability.

One heatmap is derived from empirical data, and the other heatmap is generated by an algorithm that is designed to simulate the natural process that underlies the empirical data.

I wish to tune the algorithm to make the generated heatmap match up as closely to the empirical heatmap as possible, but this is difficult without a proper metric to actually make a comparison. Thus, I wish to implement a metric that can return a value from 0 to 1 to make this comparison.

I am currently considering vector distance, mutual information, and KL-divergence. I am curious if anyone has experience or advice regarding this. --Thanks!