The Thresher: Lucky Imaging without the Waste
arXiv:2202.04686 · doi:10.1093/mnras/stac427
Abstract
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.
arXiv comment14 pages, 9 figures, Accepted for publication in Monthly Notices of the Royal Astronomical Society
References in corpus (14)
- LSST: from Science Drivers to Reference Design and Anticipated Data Products
- A method for optimal image subtraction
- Lucky Imaging: High Angular Resolution Imaging in the Visible from the Ground
- Proper image subtraction - optimal transient detection, photometry and hypothesis testing
- A New Algorithm For Difference Image Analysis
- Deconvolution with correct sampling
- The Two-Colour EMCCD Instrument for the Danish 1.54m Telescope and SONG
- High Frame-rate Imaging Based Photometry, Photometric Reduction of Data from Electron-multiplying Charge Coupled Devices (EMCCDs)
- Least-squares methods with Poissonian noise: an analysis and a comparison with the Richardson-Lucy algorithm
- High-Efficiency Lucky Imaging
- Regularization Techniques for PSF-Matching Kernels. I. Choice of Kernel Basis
- Difference image analysis: Automatic kernel design using information criteria
- Robust Statistics for Image Deconvolution
- PyTorchDIA: A flexible, GPU-accelerated numerical approach to Difference Image Analysis