Identifiability of the Simplex Volume Minimization Criterion for Blind Hyperspectral Unmixing: The No Pure-Pixel Case

In blind hyperspectral unmixing (HU), the pure-pixel assumption is well-known to be powerful in enabling simple and effective blind HU solutions. However, the pure-pixel assumption is not always satisfied in an exact sense, especially for scenarios where pixels are heavily mixed. In the no pure-pixel case, a good blind HU approach to consider is the minimum volume enclosing simplex (MVES). Empirical experience has suggested that MVES algorithms can perform well without pure pixels, although it was not totally clear why this is true from a theoretical viewpoint. This paper aims to address the latter issue. We develop an analysis framework wherein the perfect endmember identifiability of MVES is studied under the noiseless case. We prove that MVES is indeed robust against lack of pure pixels, as long as the pixels do not get too heavily mixed and too asymmetrically spread. The theoretical results are verified by numerical simulations

Efficient Clustering on Riemannian Manifolds: A Kernelised Random Projection Approach

Reformulating computer vision problems over Riemannian manifolds has demonstrated superior performance in various computer vision applications. This is because visual data often forms a special structure lying on a lower dimensional space embedded in a higher dimensional space. However, since these manifolds belong to non-Euclidean topological spaces, exploiting their structures is computationally expensive, especially when one considers the clustering analysis of massive amounts of data. To this end, we propose an efficient framework to address the clustering problem on Riemannian manifolds. This framework implements random projections for manifold points via kernel space, which can preserve the geometric structure of the original space, but is computationally efficient. Here, we introduce three methods that follow our framework. We then validate our framework on several computer vision applications by comparing against popular clustering methods on Riemannian manifolds. Experimental results demonstrate that our framework maintains the performance of the clustering whilst massively reducing computational complexity by over two orders of magnitude in some cases

An Orientation Selective Neural Network and its Application to Cosmic Muon Identification

We propose a novel method for identification of a linear pattern of pixels on a two-dimensional grid. Following principles employed by the visual cortex, we employ orientation selective neurons in a neural network which performs this task. The method is then applied to a sample of data collected with the ZEUS detector at HERA in order to identify cosmic muons which leave a linear pattern of signals in the segmented uranium-scintillator calorimeter. A two dimensional representation of the relevant part of the detector is used. The results compared with a visual scan point to a very satisfactory cosmic muon identification. The algorithm performs well in the presence of noise and pixels with limited efficiency. Given its architecture, this system becomes a good candidate for fast pattern recognition in parallel processing devices.Comment: 19 pages, 10 Postrcipt figure

Extragalactic millimeter-wave point source catalog, number counts and statistics from 771 square degrees of the SPT-SZ Survey

We present a point source catalog from 771 square degrees of the South Pole Telescope Sunyaev Zel'dovich (SPT-SZ) survey at 95, 150, and 220 GHz. We detect 1545 sources above 4.5 sigma significance in at least one band. Based on their relative brightness between survey bands, we classify the sources into two populations, one dominated by synchrotron emission from active galactic nuclei, and one dominated by thermal emission from dust-enshrouded star-forming galaxies. We find 1238 synchrotron and 307 dusty sources. We cross-match all sources against external catalogs and find 189 unidentified synchrotron sources and 189 unidentified dusty sources. The dusty sources without counterparts are good candidates for high-redshift, strongly lensed submillimeter galaxies. We derive number counts for each population from 1 Jy down to roughly 9, 5, and 11 mJy at 95, 150, and 220 GHz. We compare these counts with galaxy population models and find that none of the models we consider for either population provide a good fit to the measured counts in all three bands. The disparities imply that these measurements will be an important input to the next generation of millimeter-wave extragalactic source population models.Comment: 23 pages, 8 figures, submitted to Ap

Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers

Scene parsing, or semantic segmentation, consists in labeling each pixel in an image with the category of the object it belongs to. It is a challenging task that involves the simultaneous detection, segmentation and recognition of all the objects in the image. The scene parsing method proposed here starts by computing a tree of segments from a graph of pixel dissimilarities. Simultaneously, a set of dense feature vectors is computed which encodes regions of multiple sizes centered on each pixel. The feature extractor is a multiscale convolutional network trained from raw pixels. The feature vectors associated with the segments covered by each node in the tree are aggregated and fed to a classifier which produces an estimate of the distribution of object categories contained in the segment. A subset of tree nodes that cover the image are then selected so as to maximize the average "purity" of the class distributions, hence maximizing the overall likelihood that each segment will contain a single object. The convolutional network feature extractor is trained end-to-end from raw pixels, alleviating the need for engineered features. After training, the system is parameter free. The system yields record accuracies on the Stanford Background Dataset (8 classes), the Sift Flow Dataset (33 classes) and the Barcelona Dataset (170 classes) while being an order of magnitude faster than competing approaches, producing a 320 \times 240 image labeling in less than 1 second.Comment: 9 pages, 4 figures - Published in 29th International Conference on Machine Learning (ICML 2012), Jun 2012, Edinburgh, United Kingdo

Aerial Vehicle Tracking by Adaptive Fusion of Hyperspectral Likelihood Maps

Hyperspectral cameras can provide unique spectral signatures for consistently distinguishing materials that can be used to solve surveillance tasks. In this paper, we propose a novel real-time hyperspectral likelihood maps-aided tracking method (HLT) inspired by an adaptive hyperspectral sensor. A moving object tracking system generally consists of registration, object detection, and tracking modules. We focus on the target detection part and remove the necessity to build any offline classifiers and tune a large amount of hyperparameters, instead learning a generative target model in an online manner for hyperspectral channels ranging from visible to infrared wavelengths. The key idea is that, our adaptive fusion method can combine likelihood maps from multiple bands of hyperspectral imagery into one single more distinctive representation increasing the margin between mean value of foreground and background pixels in the fused map. Experimental results show that the HLT not only outperforms all established fusion methods but is on par with the current state-of-the-art hyperspectral target tracking frameworks.Comment: Accepted at the International Conference on Computer Vision and Pattern Recognition Workshops, 201

The Atacama Cosmology Telescope: Extragalactic Sources at 148 GHz in the 2008 Survey

We report on extragalactic sources detected in a 455 square-degree map of the southern sky made with data at a frequency of 148 GHz from the Atacama Cosmology Telescope 2008 observing season. We provide a catalog of 157 sources with flux densities spanning two orders of magnitude: from 15 to 1500 mJy. Comparison to other catalogs shows that 98% of the ACT detections correspond to sources detected at lower radio frequencies. Three of the sources appear to be associated with the brightest cluster galaxies of low redshift X-ray selected galaxy clusters. Estimates of the radio to mm-wave spectral indices and differential counts of the sources further bolster the hypothesis that they are nearly all radio sources, and that their emission is not dominated by re-emission from warm dust. In a bright (>50 mJy) 148 GHz-selected sample with complete cross-identifications from the Australia Telescope 20 GHz survey, we observe an average steepening of the spectra between 5, 20, and 148 GHz with median spectral indices of $\alpha_{\rm 5-20} = -0.07 \pm 0.06$, $\alpha_{\rm 20-148} = -0.39 \pm0.04$, and $\alpha_{\rm 5-148} = -0.20 \pm 0.03$. When the measured spectral indices are taken into account, the 148 GHz differential source counts are consistent with previous measurements at 30 GHz in the context of a source count model dominated by radio sources. Extrapolating with an appropriately rescaled model for the radio source counts, the Poisson contribution to the spatial power spectrum from synchrotron-dominated sources with flux density less than 20 mJy is C^{\rm Sync} = (2.8 \pm 0.3) \times 10^{-6} \micro\kelvin^2.Comment: Accepted to Ap

Search for time-dependent B0s - B0s-bar oscillations using a vertex charge dipole technique

We report a search for B0s - B0s-bar oscillations using a sample of 400,000 hadronic Z0 decays collected by the SLD experiment. The analysis takes advantage of the electron beam polarization as well as information from the hemisphere opposite that of the reconstructed B decay to tag the B production flavor. The excellent resolution provided by the pixel CCD vertex detector is exploited to cleanly reconstruct both B and cascade D decay vertices, and tag the B decay flavor from the charge difference between them. We exclude the following values of the B0s - B0s-bar oscillation frequency: Delta m_s < 4.9 ps-1 and 7.9 < Delta m_s < 10.3 ps-1 at the 95% confidence level.Comment: 18 pages, 3 figures, replaced by version accepted for publication in Phys.Rev.D; results differ slightly from first versio