The pervasive presence of noise corrupts the data and their interpretation implies a solution of an ill-posed inverse problem. To ensure for a stable and unique solution, probability theory allows one to convert an ill-posed problem of deductive reasoning into a well-posed problem of inference. Bayesian probability theory provides the principles of inference required to solve the ill-posed problem in image analysis. Thus, focused on interferometric ALMA image data analysis, prototype softwares are proposed to enhance the Common Astronomy Software Applications package
We present a principled Bayesian framework for signal reconstruction, in which the signal is modelle...
images are randomly generated by according to a prior probability. Bayes Formula Assumption 2: Degra...
The Atacama Large Millimeter/submillimeter Array with the planned electronic upgrades will deliver a...
Bayesian probability theory is employed to provide a stable and unique solution to the ill-posed inv...
. Sampling techniques are used to explore the Bayesian posterior density in imaging problems. Beside...
Bayes' theorem is a vehicle for incorporating prior knowledge in updating the degree of belief ...
When preparing an article on image restoration in astronomy, it is obvious that some topics have to ...
When preparing an article on image restoration in astronomy, it is obvious that some topics have to ...
Bayesian methods are being increasingly employed in many different areas of research in the physical...
Many image processing problems can be presented as inverse problems by modeling the relation of the ...
The aim of this paper is to describe a novel non-parametric noise reduction technique from the point...
. The Bayesian approach to probability theory is presented as an alternative to the currently used l...
This thesis is concerned with methods for Bayesian inference and their applications in astrophysics....
Radio astronomy image formation can be treated as a linear inverse problem. However, due to physical...
We present a Bayesian Voronoi image reconstruction ( VIR) technique for interferometric data. Bayesi...
We present a principled Bayesian framework for signal reconstruction, in which the signal is modelle...
images are randomly generated by according to a prior probability. Bayes Formula Assumption 2: Degra...
The Atacama Large Millimeter/submillimeter Array with the planned electronic upgrades will deliver a...
Bayesian probability theory is employed to provide a stable and unique solution to the ill-posed inv...
. Sampling techniques are used to explore the Bayesian posterior density in imaging problems. Beside...
Bayes' theorem is a vehicle for incorporating prior knowledge in updating the degree of belief ...
When preparing an article on image restoration in astronomy, it is obvious that some topics have to ...
When preparing an article on image restoration in astronomy, it is obvious that some topics have to ...
Bayesian methods are being increasingly employed in many different areas of research in the physical...
Many image processing problems can be presented as inverse problems by modeling the relation of the ...
The aim of this paper is to describe a novel non-parametric noise reduction technique from the point...
. The Bayesian approach to probability theory is presented as an alternative to the currently used l...
This thesis is concerned with methods for Bayesian inference and their applications in astrophysics....
Radio astronomy image formation can be treated as a linear inverse problem. However, due to physical...
We present a Bayesian Voronoi image reconstruction ( VIR) technique for interferometric data. Bayesi...
We present a principled Bayesian framework for signal reconstruction, in which the signal is modelle...
images are randomly generated by according to a prior probability. Bayes Formula Assumption 2: Degra...
The Atacama Large Millimeter/submillimeter Array with the planned electronic upgrades will deliver a...