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GIven that most microscopy has the luxury of being a simpler specific case
of the Nyquist sampling theorem, I like to simplify it to a discrete model
using a checkerboard.  I first show a grid of squares and ask, "What is the
smallest feature we can resolve on this grid?"  I then show a checkerboard
pattern next to a grid with all white squares.  I point out that in order
to resolve two objects means to be able to distinguish between two point
sources and one bigger solid source.  Therefore, you need to sample not
only the peak intensities (your resolution) but also a local minimum
between them to distinguish a pair of points from a solid object.
Therefore, you need to sample at 2x your resolution.

The hope here is to give people an intuitive sense of where Nyquist
sampling theory comes from without delving into more complex issues like
aliasing.

On Tue, Nov 10, 2020 at 8:26 AM Sara Parker <[log in to unmask]>
wrote:

> *****
> To join, leave or search the confocal microscopy listserv, go to:
> http://lists.umn.edu/cgi-bin/wa?A0=confocalmicroscopy
> Post images on http://www.imgur.com and include the link in your posting.
> *****
>
> Dale,
>
> I really like the following applets for demonstrating resolution and
> sampling in practice, and connecting theory to experimental design.
>
> http://www.iscopecalc.com
>
> https://www.olympus-lifescience.com/en/microscope-resource/primer/java/imageformation/rayleighdisks/
>
> Sara Parker
> Postdoctoral Fellow, Mouneimne Lab
> (520) 626-3860
> [log in to unmask]
> Department of Cellular & Molecular Medicine
> University of Arizona
>


-- 
Benjamin E. Smith, Ph. D.
Imaging Specialist, Vision Science
University of California, Berkeley
195 Life Sciences Addition
Berkeley, CA  94720-3200
Tel  (510) 642-9712
Fax (510) 643-6791
e-mail: [log in to unmask]
https://vision.berkeley.edu/faculty/core-grants-nei/core-grant-microscopic-imaging/