Institute of Information Theory and Automation

Publication details

Variational Bayesian Image Reconstruction with an Uncertainty Model for Measurement Localization

Conference Paper (international conference)

Šroubek Filip, Soukup Jindřich, Zitová Barbara

serial: Proc. 2016 24th European Signal Processing Conference (EUSIPCO), p. 723-727

action: 24th European Signal Processing Conference (EUSIPCO), (Budapest, HU, 29.08.2016-02.09.2016)

project(s): GA13-29225S, GA ČR, TA04011392, GA TA ČR

keywords: Variational Bayes, Image Reconstruction

preview: Download

abstract (eng):

We propose a general data acquisition model with volatile random displacement of measured samples. Discrepancies between recorded and true positions of the original data is due to the nature of measured data or the acquisition device itself. A reconstruction method based on the Variational Bayesian inference is proposed, which estimates the original data from samples acquired with the acquisition model, and its relation to Jensen’s inequality is discussed. A model variant of 2D image\nreconstruction is analyzed in detail. Further, we outline a relation between the proposed method and the classic deconvolution problem, and illustrate superiority of the Variational Bayesian approach in the case of small number of samples.


Responsible for information: admin
Last modification: 21.12.2012
Institute of Information Theory and Automation