Combining fuzzy logic and voting methods for matching pixel spectra with signature databases

This paper discusses a method for searching a database of known material signatures to find the closest match with an unknown signature. This database search method combines fuzzy logic and voting methods to achieve a high level of classification accuracy with the signatures and data cubes tested. This paper discusses the method in detail to include background and test results. It makes reference to public literature concerning components used by the method but developed elsewhere. This paper results from a project whose main objective is to produce an easily integrated software tool that makes an accurate best-guess as to the material(s) indicated by the signature of a pixel found to be "interesting" according to some analysis method, such as anomaly detection and scene characterization. Anomaly detection examines a spectral cube and determines which pixels are "unusual" relative to the majority background. Scene characterization finds pixels whose signatures are representative of the unique pixel groups. The current project fully automates the process of determining unknown pixels of interest, taking the signatures from the flagged pixels, searching a database of known signatures, and making a best guess as to the material(s) represented by each pixel's signature. The method ranks the possible materials by order of likelihood with the purpose of accounting for multiple materials existing in the same pixel. In this way it is possible to deliver multiple reportings when more than one material is closely matched within some threshold. This facilitates human analysis and decisionmaking for production purposes. The implementation facilitates rapid response to interactive analysis needs in support of strategic and tactical operational requirements in both the civil and defense sectors.