Bayesian 3D X-ray Computed Tomography with a Hierarchical Prior Model for Sparsity in Haar Transform Domain
In this paper, a hierarchical prior model based on the Haar transformation and an appropriate Bayesian computational method for X-ray CT reconstruction are presented. Given the piece-wise continuous property of the object, a multilevel Haar transformation is used to associate a sparse representation...
Main Authors: | Li Wang, Ali Mohammad-Djafari, Nicolas Gac, Mircea Dumitru |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2018-12-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/20/12/977 |
Similar Items
-
A Hierarchical Sparsity Unmixing Method to Address Endmember Variability in Hyperspectral Image
by: Jinlin Zou, et al.
Published: (2018-05-01) -
Ολοκλήρωμα Haar
by: Μακρίδης, Μιχαήλ
Published: (2009) -
FOURIER COEFFICIENTS OF CONTINUOUS FUNCTIONS WITH RESPECT TO LOCALIZED HAAR SYSTEM
by: E. S. Belkina, et al.
Published: (2017-06-01) -
Curvelet reconstruction with sparsity-promoting inversion : successes and challenges
by: Hennenfent, Gilles, et al.
Published: (2008) -
Image Compression using Haar and Modified Haar Wavelet Transform
by: Mohannad Abid Shehab Ahmed, et al.
Published: (2013-04-01)