Robotics: Science and Systems IX
Bayesian Fusion for Multi-Modal Aerial Images
Alistair Reid, Fabio Ramos, Salah SukkariehAbstract:
This paper presents a fusion method to combine aerial images from a low flying Unmanned Aerial Vehicle (UAV) with images of other spectral bands from sources such as satellites or commercial hyperspectral imagers. The proposed method propagates information from high-resolution images into other low-resolution modalities while allowing the images to have different spectral channels. This means the relationship between the high-resolution and low-resolution channels is expected to be non-deterministic, non-linear and non-stationary. A novel Gaussian Process (GP) framework was developed to define a stochastic prior over the estimated images. Its covariance function is computed to replicate the local structure of the high-resolution image, and allows the model to infer a high-resolution estimate from a low-resolution channel. Results are presented for natural images acquired by a UAV in a farmland mapping application.
Bibtex:
@INPROCEEDINGS{Reid-RSS-13, AUTHOR = {Alistair Reid AND Fabio Ramos AND Salah Sukkarieh}, TITLE = {Bayesian Fusion for Multi-Modal Aerial Images}, BOOKTITLE = {Proceedings of Robotics: Science and Systems}, YEAR = {2013}, ADDRESS = {Berlin, Germany}, MONTH = {June}, DOI = {10.15607/RSS.2013.IX.025} }