High-Fidelity Imaging Using Compact Multi-Frame Blind Deconvolution

  • Douglas A. HopeEmail author
  • Stuart M. Jefferies
  • Cody Smith


Multi-frame blind deconvolution (MFBD) has been a cornerstone for ground-based space situational awareness of near-Earth satellites since the early 2000’s. In 2011 a variation of the classic MFBD algorithm was introduced that required solving for fewer variables than in the classic algorithm, but which still used all the available data to constrain the solution. The initial application of the new approach, referred to as compact multi-frame blind deconvolution (CMFBD), was found to be significantly faster than MFBD, and showed an indication that it may be able to provide restorations of higher quality, i.e. fewer artifacts. Since its introduction, the CMFBD approach has become the foundation of several MFBD-based algorithms that have been developed for applications such as high-accuracy wave front sensing from image plane data, and imaging through strong turbulence: both of which contribute to space situational awareness by increasing the area of sky available for surveillance. Here we show that the performance of the CMFBD approach can be improved through the addition of a new ”internal consistency” constraint on the estimated point-spread functions.


Blind deconvolution Speckle imaging Atmospheric turbulence Image restoration 



This work was supported by award FA9550-14-1-0178 from the Air Force Office of Scientific Research.


  1. 1.
    Schulz, T.J.: Multi-frame blind deconvolution of astronomical images. JOSA A. 10, 1064–1073 (1993)CrossRefGoogle Scholar
  2. 2.
    Jefferies, S.M., Christou, J.: Restoration of astronomical images by iterative blind deconvolution. ApJ 415, 862–864 (1993)CrossRefGoogle Scholar
  3. 3.
    Hope, D.A., Jefferies, S.M.: Compact multi-frame blind deconvolution. Opt. Lett. 36, 867–869 (2011)CrossRefGoogle Scholar
  4. 4.
    Hope, D., Jefferies, S.M.: Multi-frame blind deconvolution: compact and multi-channel versions. In: Ryan, S. (ed.) Proceedings of the Advanced Maui Optical and Space Surveillance Technologies Conference, p E39. The Maui Economic Development Board, Held in Wailea (2011)Google Scholar
  5. 5.
    Hope, D., Jefferies, S.M., Hart, M., Nagy, J.: High-resolution speckle imaging through strong atmospheric turbulence. Opt. Express 24, 12116–12129 (2016)CrossRefGoogle Scholar
  6. 6.
    Matson, C.L., Borelli, K., Jefferies, S.M., Hege, E.K., Beckner, C.C., Lloyd-Hart, M.: A fast and optimal Multi-Frame blind deconvolution algorithm for High-Resolution, Ground-Based imaging of space objects. Appl. Opt. 48, A75–A92 (2009)CrossRefGoogle Scholar

Copyright information

© American Astronautical Society 2019

Authors and Affiliations

  1. 1.Hope Scientific Renaissance LLCColorado SpringsUSA
  2. 2.Georgia State UniversityAtlantaUSA

Personalised recommendations