  Idier et al. [IEEE Trans. Comput. Imaging 4(1), 2018] propose a method which
achieves superresolution in the microscopy setting by leveraging random speckle
illumination and knowledge about statistical second order moments for the
illumination patterns and model noise. This is achieved without any assumptions
on the sparsity of the imaged object. In this paper, we show that their
technique can be extended to photoacoustic tomography. We propose a simple
algorithm for doing the reconstruction which only requires a small number of
linear algebra steps. It is therefore much faster than the iterative method
used by Idier et al. We also propose a new representation of the imaged object
based on Dirac delta expansion functions.
