Segmentation-based cNMF for hyperspectral unmixing

This paper presents a modification to the cNMF for unmixing where the image is first segmented and the cNMF is applied to individual segments for endmember extraction. Extracted spectral endmembers from individual segments are clustered in endmember classes to describe the entire image. The approach is compared with the global cNMF. The segmentation-based cNMF better captures subtle differences between spectrally similar classes. Experimental results are presented using an image chip from an AVIRIS image collected over AP Hill.