Butterfly transforms for efficient representation of spatially variant point spread functions in bayesian imaging

HIGHLIGHTS

• who: Vincent Eberle and colleagues from the Max Planck Institute for Astrophysics, Karl-Schwarzschild-Strau00dfe, Garching, Germany have published the article: Butterfly Transforms for Efficient Representation of Spatially Variant Point Spread Functions in Bayesian Imaging, in the Journal: Entropy 2023, 25, 652. of /2023/
• what: The authors combine them in several ways into networks compare the different architectures with respect to their performance and identify a representation that is suitable for the efficient representation of a synthetic spatially variant point spread function up to a 1% error. The authors show its application in a short . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.