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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Thompson, D.R. Mandrake, L. Gilmore, M.S. Castaño, R. |
| Copyright Year | 1980 |
| Abstract | Superpixels are homogeneous image regions comprised of multiple contiguous pixels. Superpixel representations can reduce noise in hyperspectral images by exploiting the spatial contiguity of scene features. This paper combines superpixels with endmember extraction to produce concise mineralogical summaries that assist in browsing large image catalogs. First, a graph-based agglomerative algorithm oversegments the image. We then use segments' mean spectra as input to existing statistical endmember detection algorithms such as sequential maximum angle convex cone (SMACC) and N-FINDR. Experiments compare automatically detected endmembers to target minerals in an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) scene of Cuprite, Nevada. We also consider a planetary science data set from the Compact Reconnaissance Imaging Spectrometer (CRISM) instrument that benefits from spatial averaging due to higher noise. In both cases, superpixel representations significantly reduce the computational complexity of later processing while improving endmembers' match to the target spectra. |
| Sponsorship | IEEE Geoscience and Remote Sensing Society IEEE URSI |
| Starting Page | 4023 |
| Ending Page | 4033 |
| Page Count | 11 |
| File Size | 1729654 |
| File Format | |
| ISSN | 01962892 |
| Volume Number | 48 |
| Issue Number | 11 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-11-01 |
| Publisher Place | U.S.A. |
| Access Restriction | One Nation One Subscription (ONOS) |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Pixel Image segmentation Noise Hyperspectral imaging Instruments Minerals superpixels Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Compact Reconnaissance Imaging Spectrometer (CRISM) endmember detection hyperspectral images planetary geology segmentation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Earth and Planetary Sciences Electrical and Electronic Engineering |
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