Robotics: Science and Systems IX

Bayesian Fusion for Multi-Modal Aerial Images

Alistair Reid, Fabio Ramos, Salah Sukkarieh

Abstract:

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.

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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} 
}