  In traditional lucky imaging (TLI), many consecutive images of the same scene
are taken with a high frame-rate camera, and all but the sharpest images are
discarded before constructing the final shift-and-add image. Here we present an
alternative image analysis pipeline -- The Thresher -- for these kinds of data,
based on online multi-frame blind deconvolution. It makes use of all available
data to obtain a best estimate of the astronomical scene in the context of
reasonable computational limits; it does not require prior estimates of the
point-spread functions in the images, or knowledge of point sources in the
scene that could provide such estimates. Most importantly, the scene it aims to
return is the optimum of a justified scalar objective based on the likelihood
function. Because it uses the full set of images in the stack, The Thresher
outperforms TLI in signal-to-noise; as it accounts for the individual-frame
PSFs, it does this without loss of angular resolution. We demonstrate the
effectiveness of our algorithm on both simulated data and real
Electron-Multiplying CCD images obtained at the Danish 1.54m telescope (hosted
by ESO, La Silla). We also explore the current limitations of the algorithm,
and find that for the choice of image model presented here, non-linearities in
flux are introduced into the returned scene. Ongoing development of the
software can be viewed at https://github.com/jah1994/TheThresher.
