Multiple Instance Hyperspectral Target Characterization
In this paper, two methods for multiple instance target characterization, MI SMF and MI ACE, are presented. MI SMF and MI ACE estimate a discriminative target signature from imprecisely labeled and mixed training data. In many applications, such as sub pixel target detection in remotely sensed hyperspectral imagery, accurate pixel level labels on training data is often unavailable and infeasible to obtain. Furthermore, since sub pixel targets are smaller in size than the resolution of a single pixel, training data is comprised only of mixed data points (in which target training points are mixtures of responses from both target and non target classes) Results show improved, consistent performance over existing multiple instance concept learning methods on several hyperspectral sub pixel target detection problems.
ArXiv