Image Fusion Using Belief Propagation

Paul R. Hill; David R. Bull

ICASSP 2018accepted0 citations

Image Fusion Using Belief Propagation

Abstract

This paper describes the application of belief propagation methods to image fusion within a complex wavelet decomposition (the Dual Tree Complex Wavelet Transform: DT-CWT). Belief propagation within each transform subband iterates through a lattice based Bayesian belief network. This leads to precisely controlled spatial coherence of subband coefficient fusion through the definition of belief graph probabilities. This results in a significant improvement in quantitatively measured fusion performance for a large database of over 160 fusion image pairs from a range of fusion applications including remote sensing, multi-focus and multi-modal sources. Improvements in qualitative image fusion performance is also demonstrated.

BibTeX

@inproceedings{icassp2018_imagefusionusing,
  title = {Image Fusion Using Belief Propagation},
  author = {Paul R. Hill and David R. Bull},
  booktitle = {ICASSP 2018},
  year = {2018}
}