Automated analysis of radar imagery of Venus: handling lack of ground truth
Lack of verifiable ground truth is a common problem in remote sensing image analysis. For example, consider the synthetic aperture radar (SAR) image data of Venus obtained by the Magellan spacecraft. Planetary scientists are interested in automatically cataloging the locations of all the small volcanoes in this data set; however, the problem is very difficult and cannot be performed with perfect reliability even by human experts. Thus, training and evaluating the performance of an automatic algorithm on this data set must be handled carefully. We discuss the use of weighted free-response receiver-operating characteristics (wFROCs) for evaluating detection performance when the "ground truth" is subjective. In particular, we evaluate the relative detection performance of humans and automatic algorithms. Our experimental results indicate that proper assessment of the uncertainty in "ground truth" is essential in applications of this nature.
© 1994. Date of Current Version: 06 August 2002. The authors would like to thank Jayne Aubele and Larry Crumpler of the Department of Geological Sciences, Brown University, for their assistance in labelling images, and Maureen Burl (JPL) for assistance with the experiments. The research described in this paper was carried out by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Published - BURicip94.pdf