Image differencing with fuzzy overlay?

[StefanoPotter]

I have 80 Landsat images, and I have calculated 5 vegetative indices for each one and then created a fuzzy overlay of the indices.  So I have 80 images that are fuzzy overlays.  My question is, would it be practical to do image differencing using these fuzzy overlays?  For instance, a NDVI value of 0.7 means the same thing in all image dates, but does a fuzzy overlay value of 0.7 mean the same thing between images?  Or is it being scaled in each image according to the rest of the values? 

[DanPatterson_Retired]

NDVI is a ratio, hence it standardized based on proportional differences...so a 0.7 of a ratio is a ratio of a ratio.  IF you do the math, you can see that the a specific numeric value can be derived at using different inputs as long as they behave in the same fashion.  In short... you will be fuzzifying too much...but other opinions may be different than mine.  I have never been a big fan of ratios/indices unless the absolutes that went into their calculation are reported as well and 100% of the people in here agree with me (room population=1)

[PROBERT68]

Wikipedia has information about NDVI here Normalized Difference Vegetation Index - Wikipedia, the free encyclopedia