Learn More
Mustard spinach plants were grown in mercury-spiked and contaminated soils collected in the field under controlled laboratory conditions over a full growth cycle to test if vegetation grown in these soils has discernible characteristics in visible/near-infrared (VNIR) spectra. Foliar Hg concentrations (0.174-3.993ppm) of the Mustard spinach plants were(More)
In the era of large scientific data sets, there is an urgent need for methods to automatically prioritize data for review. At the same time, for any automated method to be adopted by scientists, it must make decisions that they can understand and trust. In this paper, we propose Discovery through Eigenbasis Modeling of Uninteresting Data (DEMUD), which uses(More)
Introduction: Martian gullies were first identified by Malin and Edgett [1]. Previous work [2] has examined the characteristics of gullies in the southern hemisphere in detail. Less detailed work has been done for the northern hemisphere [3,4]. Gullies are found predominantly in the midlatitudes of both hemispheres between 30°-50° [1,2], which implies a(More)
Introduction: Tellus Regio is a plateau-shaped highland in the northern hemisphere of Venus largely composed of tessera terrain characterized by complex deformation comprising at least two sets of intersecting ridges and grooves which contribute to high radar backscatter [1,2; Fig. 1]. Stratigraphic studies of tessera terrain occurrences establish that they(More)
—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.(More)
The science return from future robotic exploration of the martian surface can be enhanced by performing routine processing using on board computers. This can be accomplished by using software that recognizes scientifically relevant surface features from imaging and other data and prioritizes the data for return transmission to Earth. Two algorithms have(More)
Fast automated analysis of hyperspectral imagery can inform observation planning and tactical decisions during planetary exploration. Products such as mineralogical maps can focus analysts' attention on areas of interest and assist data mining in large hyperspectral catalogs. In this work, sparse spectral unmixing drafts mineral abundance maps with Compact(More)
—We have developed an artificial neural network (ANN) based carbonate detector capable of running on current and future rover hardware. The detector can identify calcite in visible/NIR (350–2500 nm) spectra of both laboratory specimens covered by ferric dust and rocks in Mars analogue field environments. The ANN was trained using the Backpropagation(More)
We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing(More)
[1] We present a semiautomated method to extract spectral end‐members from hyperspectral images. This method employs superpixels, which are spectrally homogeneous regions of spatially contiguous pixels. The superpixel segmentation is combined with an unsupervised end‐member extraction algorithm. Superpixel segmentation can complement per pixel(More)