  Imaging beyond the diffraction limit barrier has attracted wide attention due
to the ability to resolve image features that were previously hidden. Of the
various super-resolution microscopy techniques available, a particularly simple
method called saturated excitation microscopy (SAX) requires only a simple
modification of a laser scanning microscope where the illumination beam power
is sinusoidally modulated and driven into saturation. SAX images are extracted
from harmonics of the modulation frequency and exhibit improved spatial
resolution. Unfortunately, this elegant strategy is hindered by the incursion
of shot noise that prevents high resolution imaging in many realistic
scenarios. Here, we demonstrate a new technique for super resolution imaging
that we call computational saturated absorption (CSA) in which a joint
deconvolution is applied to a set of images with diversity in spatial frequency
support among the point spread functions used in the image formation with
saturated laser scanning fluorescence microscope. CSA microscopy allows access
to the high spatial frequency diversity in a set of saturated effective point
spread functions, while avoiding image degradation from shot noise.
