I am using R's spatstat package to analyze spatial patterns of objects across plant leaves.
Let's say I have 10 leaves, each with corresponding X,Y coordinates of the objects and a window in the shape of a leaf. Each leaf is differently sized and each image containing the leaf may have varying dimensions.
I would like to take the separate point patterns, and create one "average" point pattern, with a corresponding heat map. Due to the different sizes, differently shaped/sized windows, is there a way to create a composite pattern from this data?
I have analyzed all the patterns, etc. separately, but would like to be able to view a composite visual pattern. Is there a machine learning exercise I could use?
Apologies if this does not make sense, this is not my area of expertise.
Example tesselations for each leaf: