  Super-resolution microscopy has revolutionized optical fluorescence imaging
by improving 3D resolution by 1-2 orders of magnitude. While different methods
can successfully increase the resolution, all methods share significant
differences with standard imaging methods, making the usual measures of
resolution inapplicable. In particular image quality and information content
are spatially heterogeneous with variabilities that can be comparable to their
mean values, limiting the use of the average resolution as a predictor for
local information. A common use of super-resolution data is to test or
establish structural models, and in these cases it would be valuable to assess
the capacity of the data to validate a model. We focus here on single-molecule
localization methods and present a new way of assessing the quality and
reliability of super-resolution data.
