Space object images obtained through ground-based telescopes tend to be heavily blurred and degraded by the atmospheric turbulence as well as detection noise and aberrations of optical systems. Multi-Frame Blind Deconvolution (MFBD) is currently the mainstream image restoration algorithm for images degraded by the atmospheric turbulence. MFBD jointly estimates the original image of object and the corresponding point spread functions (PSFs) from a sequence of short-exposure images. From our experience, there are still a lot of space for the improvement of the traditional MFBD algorithm. The mixed-Gaussian noise model that accounts for both the photonic and detector noise is used to replace the stationary Gaussian noise model. The L2-L1 (quadratic-linear) regularization method is used to replace originally used TV regularization method or Tikhonov regularization method. The phase annealing method is used to improve the quality of initial phase estimation and the multi-round iterative MFBD algorithm is preliminarily implemented. The simulation results demonstrate that the restored images obtained by the multi-round iterative MFBD algorithm often have better quality than that restored by traditional MFBD.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.