Abstract: A number of noteworthy techniques have been put forth recently in different research fields for comparing clusterings. Herein, we introduce a new method for comparing soft (fuzzy, probabilistic, and possibilistic) partitions based on the earth mover’s distance (EMD) and… Read More
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Subpixel target detection in hyperspectral imagery using piece-wise convex spatial-spectral unmixing, possibilistic and fuzzy clustering, and co-registered LiDAR
Abstract: A new algorithm for subpixel target detection in hyperspectral imagery is proposed which uses the PFCM-FLICM-PCE algorithm to model and estimate the parameters of the image background. This method uses the piece-wise convex mixing model with spatial-spectral constraints, and… Read More
Simultaneous band-weighting and spectral unmixing for multiple endmember sets
Abstract: In this paper, the SimUltaneous Band-weighting and Spectral Unmixing for Multiple Endmember Sets (SUBSUME) which performs endmember extraction for multiple sets of endmembers, estimates proportion values, and assigns partition-specific band weights is presented. By incorporating simultaneous band weighting, input… Read More
Multi-Image texton selection for sonar image seabed co-segmentation
Abstract: In this paper we describe an unsupervised approach to seabed co-segmentation over the multiple sonar images collected in sonar surveys. We adapt a traditional single image segmentation texton-based approach to the sonar survey task by modifying the texture extraction… Read More
Landmine classification using possibilistic K-nearest neighbors with wideband electromagnetic induction data
Abstract: A possibilistic K-Nearest Neighbors classifier is presented to classify mine and non-mine objects using data collected from a wideband electromagnetic induction (WEMI) sensor. The proposed classifier is motivated by the observation that buried objects often have consistent signatures depending… Read More
Spectral unmixing using the beta compositional model
Abstract: This paper introduces a beta compositional model as a mixing model for hyperspectral images. Endmembers are represented via beta distributions, hereafter referred to as betas, to constrain endmembers to a physically-meaningful range. Two associated spectral unmixing algorithms are described… Read More
Piecewise convex multiple-model endmember detection and spectral unmixing
Abstract: A hyperspectral endmember detection and spectral unmixing algorithm that finds multiple sets of endmembers is presented. Hyperspectral data are often nonconvex. The Piecewise Convex Multiple-Model Endmember Detection algorithm accounts for this using a piecewise convex model. Multiple sets of… Read More
A framework for computing crowd emotions using agent based modeling
Abstract: We present a computational framework for modeling geospatial dynamics of crowd emotions as part of anticipatory analysis. The framework is based on agent based modeling (ABM) and evaluation-activation space for emotion representation. ABM is a simulation technique that uses… Read More
Sampling piecewise convex unmixing and endmember extraction
Abstract: A Metropolis-within-Gibbs sampler for piecewise convex hyperspectral unmixing and endmember extraction is presented. The standard linear mixing model used for hyperspectral unmixing assumes that hyperspectral data reside in a single convex region. However, hyperspectral data are often nonconvex. Furthermore,… Read More
Landmine classification using possibilistic K-nearest neighbors with wideband electromagnetic induction data
Abstract: In this thesis, a possibilistic K-nearest neighbor classifier is presented to distinguish between and classify mine and non-mine targets on data obtained from wideband electromagnetic induction sensors. The goal of this work is to develop methods for classifying wide-band… Read More