An unstructured sub-pixel target detector for hyperspectral imagery

As the spatial resolution of hyperspectral imagery is usually limited, sub-pixel targets only occupy part of the pixel area. Unstructured detectors, such as adaptive cosine estimate (ACE), has shown promising performance in sub-pixel targets detection, which models the background with a distribution property. This paper proposes a unstructured detector in which selective endmembers are used according to different pixels to ensure that the true composition of endmembers in each pixel is utilized in both the subspace model and the statistical test. Experiments show its better performance for sub-pixel targets detection than other unstructured detector.