by Csaba Benedek, Tamas Sziranyi, Zoltan Kato, Josiane Zerubia
Abstract:
We propose a new Bayesian method for detecting the regions of object displacements in aerial image pairs. We use a robust but coarse 2D image registration algorithm. Our main challenge is to eliminate the registration errors from the extracted change map. We introduce a three-layer Markov random field (L^3MRF) model which integrates information from two different features, and ensures connected homogenous regions in the segmented images. Validation is given on real aerial photos.
Reference:
Csaba Benedek, Tamas Sziranyi, Zoltan Kato, Josiane Zerubia, Detection of Object Motion Regions in Aerial Image Pairs with a Multilayer Markovian Model, In IEEE Transactions on Image Processing, volume 18, no. 10, pp. 2303-2315, 2009, IEEE.
Bibtex Entry:
@string{tip="IEEE Transactions on Image Processing"}
@Article{Benedek-etal2009,
author = {Csaba Benedek and Tamas Sziranyi and Zoltan Kato and
Josiane Zerubia},
title = {Detection of Object Motion Regions in Aerial Image
Pairs with a Multilayer {M}arkovian Model},
journal = tip,
year = 2009,
publisher = IEEE,
volume = 18,
number = 10,
pages = {2303--2315},
month = oct,
abstract = {We propose a new Bayesian method for detecting the
regions of object displacements in aerial image
pairs. We use a robust but coarse 2D image
registration algorithm. Our main challenge is to
eliminate the registration errors from the extracted
change map. We introduce a three-layer Markov random
field (L^3MRF) model which integrates information
from two different features, and ensures connected
homogenous regions in the segmented
images. Validation is given on real aerial photos.},
pdf = {papers/tip2009.pdf}
}