2010

Sparse Superpixel Unmixing for Hyperspectral Image Analysis

Software was developed that automatically detects minerals that are present in each pixel of a hyperspectral image. An algorithm based on sparse spectral unmixing with Bayesian Positive Source Separation is used to produce mineral abundance maps from hyperspectral images. A “superpixel” segmentation strategy enables efficient unmixing in an interactive session.

Subwindow of Observation demonstrates superpixel segmentation. Left: original subimage. Center: coarse segmentation, minimum region size 100. Right: fine segmentation, minimum region size 20." class="caption" align="left">The algorithm computes statistically likely combinations of constituents based on a set of possible constituent minerals whose abundances are uncertain. A library of source spectra from laboratory experiments or previous remote observations is used. A superpixel segmentation strategy improves analysis time by orders of magnitude, permitting incorporation into an interactive user session (see figure).

Mineralogical search strategies can be categorized as “supervised” or “unsupervised.” Supervised methods use a detection function, developed on previous data by hand or statistical techniques, to identify one or more specific target signals. Purely unsupervised results are not always physically meaningful, and may ignore subtle or localized mineralogy since they aim to minimize reconstruction error over the entire image. This
algorithm offers advantages of both methods, providing meaningful physical interpretations and sensitivity to subtle or unexpected minerals.

This work was done by Rebecca Castano and David R. Thompson of Caltech and Martha Gilmore of Wesleyan University for NASA’s Jet Propulsion Laboratory. For more information, contact This email address is being protected from spambots. You need JavaScript enabled to view it..

The software used in this innovation is available for commercial licensing. Please contact Daniel Broderick of the California Institute of Technology at danielb@ caltech.edu. Refer to NPO-47038.

White Papers

Next-Generation, Miniature High Voltage Power Modules
Sponsored by EMCO High Voltage
Tubing & Hose Buying Tips
Sponsored by Newage Industries
Serial Fabrics Improve System Design
Sponsored by Pentek
9 Questions to Ask when Specifying a Slewing Ring Bearing
Sponsored by Kaydon
How to Design Your Part for Direct Digital Manufacturing
Sponsored by Stratasys
T&M Solutions for Software Defined Radios (SDR)
Sponsored by Rohde and Schwarz A and D

White Papers Sponsored By: