Rescuing operators of small recreational vessels is a constant resource drain on the limited operating budget of the Canadian Coast Guard. As a result, a new and innovative application of small target surveillance techniques is being developed at the Department of Geodesy and Geomatics Engineering, UNB, Canada. This work is being done in support of the development of a strategic decision making tool based on risk modeling to be used to predict where in Canadian
waters marine incidents are most likely to occur in support of best resource allocation.
Previous research in the use of hyperspectral imaging for search and rescue, resulted in the development of fast, nonparametric
"spatio-spectral" template subpixel object detection algorithm. The results of this work are being adapted and enhanced for use with the new, commercially available spaceborne high-resolution optical imagery. Investigations are being made regarding the utility of the Minkowski distance metrics for use in small target detection within a
multispectral imagery environment. Further, research is being performed on the employment of the Mahalanobis distance metric to enhance the "spatio-spectral" template by exploiting the variance/covariance information surrounding a potential target.
The detection results for the two target vessels were excellent using the Manhattan and Euclidean distance. The best results were had using the Manhattan distance metric with a 5x5 kernel with all 16 yachts detected, no false negatives, and six false positives.