Astronomy and Astrophysics – Astrophysics
Scientific paper
Dec 1994
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1994a%26as..108..409b&link_type=abstract
Astronomy and Astrophysics Suppl. 108, 409-415 (1994)
Astronomy and Astrophysics
Astrophysics
5
Methods: Data Analysis, Methods: Statistical, Techniques: Image Processing
Scientific paper
We propose a simulation-based bootstrap method to access global significance levels of deconvolution models in the Richardson-Lucy and other iterative restoration algorithms that converge locally. These significance levels allow one to check at each iterative step how good the model is and when iterations can be stopped. Adding more iterations in the deconvolution improves the fitting but is very slow at later time; while too much entropy or smoothness will be lost in the models. A good deconvolution model should firstly have a significance level as high as possible (>=20%), and secondly, be as smooth as possible. We have used two examples to illustrate how such models can be derived in practice. We point out that maximizing the sum of the likelihood of fitting and a priori entropy does not guarantee an acceptable significance level for the resulting model. If one's a priori knowledge is too poor, the model may not be able to fit the data at a reasonable significance level. Instead, a maximum-entropy-like iterative restoration algorithm can be performed later by acquiring a priori knowledge from the Richardson-Lucy restoration. However, this is necessary only when it does increase the levels significantly.
Bi Hongguang
Boerner Gerhard
No associations
LandOfFree
When does the Richardson-Lucy deconvolution converge? does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with When does the Richardson-Lucy deconvolution converge?, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and When does the Richardson-Lucy deconvolution converge? will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1318134