I am using ENVI 5.3 to classify a Region of Interest clipped from Landsat 8 OLI. I have already performed calibration of my DNs by transforming it into Radiance and derived Reflectance image using FLAASH atmospheric correction module provided in ENVI. Afterward, I have re-scaled the output (Reflectance Values) to 1-0 scale prior to extract landcover classes from the scene.
Apparently, there is minute difference of Reflectance between builtup/impervious surfaces and exposed bedrocks. Using, Maximum Liklihood Classification doesn't seems to be working for the reason. It places both materials in a single class.
Manually editing the derived landcover classes like 'recoding' from vectors or masking such pixels prior to classification and afterward combine masked pixels to desired class is hectic task when we are dealing with large areas having similar spectral issues.
Have a look on the below scene and spectral profiles of the both materials and suggest how could I deal with these pixels having almost similar reflectance responses.
What is the optimal way to classify such scene?