A novel spectral fringe-adjusted joint transform (SFJTC) correlation based technique is proposed for detecting very small targets involving only a few pixels in hyperspectral imagery. In this technique, spectral signatures from the unknown hyperspectral imagery are correlated with the reference signature using the SFJTC technique. This technique can detect both single and/or multiple desired targets in constant time while accommodating the in-plane and out-of-plane distortions. Furthermore, in this paper, a new metric, called the peak-to-clutter mean, is introduced that provides sharp and high correlation peaks corresponding to targets and makes the proposed technique intensity invariant. Test results using real life hyperspectral image datacubes are presented to verify the effectiveness of the proposed technique.
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