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The number of pixels in a hyperspectral image is one of the main reasons that affects pixel unmixing (especially end-member extraction). Superpixel segmentation techniques can compose adjacent pixels with similar characteristics into image blocks, and retain useful information for further image processing, thereby significantly reduce the number of pixels involved in endmember extraction and solve...
The Compressive-Projection Principle Component Analysis (CPPCA) technique which recovers hyperspectral image(HSI) data from random projection efficiently, has been proved to be significant in decreasing signal-sensing costs at the sender. Inspired by the fact that the spectral signature of the same ground cover is similar, and two pixels of the neighborhood are likely to belonging to the same ground...
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