Helper function for handling diverse input data types

[k034b363]

Is your feature request related to a problem? Please describe.
Across several applications, including geospatial data and certain spectral indices, data types and ranges can vary. It would be helpful to have a more comprehensive way of deciding what data type is and how it might best be scaled for either visualization or calculation downstream.

Describe the solution you'd like
A helper function that would take a numpy array and through both the data type and range, decide how to scale or transform the array into something more uniform (or at least so that all input types might be visualized in the same way for geospatial, for example).

Describe alternatives you've considered
Something specific to read_geotif in plantcv-geospatial, but the work involved would probably be best incorporated into main plantcv in case it is of use more broadly

[HaleySchuhl]

This is a great idea. Checking datatypes can be a helper function, since it's something that comes up very often. This feels related to this issue #1635, though these examples of datatype checks are mostly between binary, grayscale, and RGB.