Chester rlson Center For Imaging Science

Rochester, NY, United States

Chester rlson Center For Imaging Science

Rochester, NY, United States

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Principe D.A.,Diego Portales University | Sacco G.G.,National institute for astrophysics | Kastner J.H.,Chester rlson Center For Imaging Science | Wilner D.,Harvard - Smithsonian Center for Astrophysics | And 2 more authors.
Astronomy and Astrophysics | Year: 2017

We present Chandra X-ray Observatory and Submillimeter Array (SMA) imaging of HBC 515, a system consisting of multiple young stellar objects (YSOs). The five members of HBC 515 represent a remarkably diverse array of YSOs, ranging from the low-mass Class I/II protostar HBC 515B, through Class II and transition disk objects (HBC 515D and C, respectively), to the "diskless", intermediate-mass, pre-main sequence (pre-MS) binary HBC 515A. Our Chandra/ACIS imaging establishes that all five components are X-ray sources, with HBC 515A-a subarcsecond-separation binary that is partially resolved by Chandra-being the dominant X-ray source. We detect an X-ray flare associated with HBC 515B. In the SMA imaging, HBC 515B is detected as a strong 1.3 mm continuum emission source; a second, weaker mm continuum source is coincident with the position of the transition disk object HBC 515C. These results strongly support the protostellar nature of HBC 515B, and firmly establish HBC 515A as a member of the rare class of relatively massive, X-ray luminous weak-lined T Tauri stars that are binaries and have shed their disks at very early stages of pre-MS evolution. The coexistence of two such disparate objects within a single, presumably coeval multiple YSO system highlights the influence of pre-MS star mass, binarity, and X-ray luminosity in regulating the lifetimes of circumstellar, planet-forming disks, and the timescales of star-disk interactions. © 2017 ESO.


Vodacek A.,Chester rlson Center For Imaging Science | Kerekes J.P.,Chester rlson Center For Imaging Science
Procedia Computer Science | Year: 2012

The generalized optical remote sensing tracking problem for an object moving in a dynamic urban environment is complex. Two emerging capabilities that can help solve this problem are adaptive multimodal sensing and modeling with data assimilation. Adaptive multimodal sensing describes sensor hardware systems that can be rapidly reconfigured to collect the appropriate data as needed. Imaging of a moving target implies some ability to forecast where to image next so as to keep the object in the scene. Forecasts require models and to help solve this prediction problem, data assimilation techniques can be applied to update executing models with sensor data and thereby dynamically minimize forecast errors. The direct combination of these two capabilities is powerful but does not answer the questions of how or when to change the imaging modality. The Dynamic Data-Driven Applications Systems (DDDAS) paradigm is well-suited for solving this problem, where sensing must be adaptive to a complex changing environment and where the prediction of object movement and its interaction with the environment will enhance the ability of the sensing system to stay focused on the object of interest. Here we described our work on the creation of a modeling system for optical tracking in complex environments, with a focus on integrating an adaptive imaging sensor within the system framework. © 2012 Published by Elsevier Ltd.


Uzkent B.,Chester rlson Center For Imaging Science | Vodacek A.,Chester rlson Center For Imaging Science | Kerekes J.P.,Chester rlson Center For Imaging Science | Chen B.,Chester rlson Center For Imaging Science
Procedia Computer Science | Year: 2013

We consider the optical remote sensing tracking problem for vehicles in a complex environment using an adaptive sensor that can take spectral data at a small number of locations. The Dynamic Data-Driven Applications Systems (DDDAS) paradigm is well-suited for dynamically controlling such an adaptive sensor by using the prediction of object movement and its interaction with the environment to guide the location of spectral measurements. The spectral measurements are used for target identification through feature matching. We consider several adaptive sampling strategies for how to assign locations for spectral measurements in order to distinguish between multiple targets. In addition to guiding the measurement process, the tracking system pulls in additional data from OpenStreetMap to identify road networks and intersections. When a vehicle enters a detected intersection, it triggers the use of a multiple model prediction system to sample all possible turning options. The result of this added information is more accurate predictions and analysis from data assimilation using a Gaussian Sum filter (GSF). © 2013 The Authors. Published by Elsevier B.V.


David F.,Monash University | James S.D.,University of Edinburgh | Marek J.K.,Royal Observatory Greenwich | Michael J.I.B.,Monash University | And 5 more authors.
Monthly Notices of the Royal Astronomical Society | Year: 2013

We present deep Hubble Space Telescope (HST)/Wide-Field Planetary Camera 2 (WFPC2), rest-frame U images of 17L quasars at z-1 and 2 (V and I bands, respectively), designed to explore the host galaxies.We fit the images with simple axisymmetric galaxy models, including a point source, in order to separate nuclear and host-galaxy emission. We successfully model all of the host galax es, with luminosities stable to within 0.3 mag. Combining with our earlier Near Infrared Camera and Multi-Object Spectrometer rest-frame optical study of the same sample, we provide the first rest-frame U - V colours for a sample of quasar host galaxies. While the optical luminosities of theirhost galaxies indicate that they are drawn purely from the most massive (L) early-type galaxy population, their colours are systematically bluer than those of comparably massive galaxies at t e same redshift. The host galaxies of the radioloud quasars (RLQs) in our sample are more luminousthan their radio-quiet quasar (RQQ) counterparts at each epoch, but have indistinguishable colours, confirming that the RLQs are drawn from only the most massive galaxies (1011-1012M even at z - 2), while the RQQs are slightly less massive (1011M). This is consistent with the well-known anticorrelation between radio-loudness and accretion rate. Using simple stellar population 'frosting' models, we estimate mean star formation rates of 350M yr-1 for the RLQs and 100M yr-1 forthe RQQs at z - 2. By z - 1, these rates have fallen to 150M yr-1 for the RLQs and 50M yr-1 for the RQQs.We conclude that while the host galaxies are extremely massive, they remain actively star forming at, or close to, the epoch of the quasar ©2012 The Authors.


Kastner J.H.,Chester rlson Center For Imaging Science | Qi C.,Harvard - Smithsonian Center for Astrophysics | Gorti U.,Search for Extraterrestrial Intelligence Institute | Gorti U.,NASA | And 7 more authors.
Astrophysical Journal | Year: 2015

We have used the Submillimeter Array to image, at ∼1.″5 resolution, C2H emission from the circumstellar disk orbiting the nearby (D = 54 pc), ∼8 Myr-old, ∼0.8 classical T Tauri star TW Hya. The SMA imaging reveals that the C2H emission exhibits a ring-like morphology. Based on a model in which the C2H column density follows a truncated radial power-law distribution, we find that the inner edge of the ring lies at ∼45 AU, and that the ring extends to at least ∼120 AU. Comparison with previous (single-dish) observations of C2H emission indicates that the C2H molecules are subthermally excited and, hence, that the emission arises from the relatively warm ( K), tenuous ( cm-3) upper atmosphere of the disk. Based on these results and comparisons of the SMA C2H map with previous submillimeter and scattered-light imaging, we propose that the C2H emission most likely traces particularly efficient photo-destruction of small grains and/or photodesorption and photodissociation of hydrocarbons derived from grain ice mantles in the surface layers of the outer disk. The presence of a C2H ring in the TW Hya disk hence likely serves as a marker of dust grain processing and radial and vertical grain size segregation within the disk. © 2015. The American Astronomical Society. All rights reserved.


Kastner J.H.,Chester rlson Center For Imaging Science | Qi C.,Harvard - Smithsonian Center for Astrophysics | Gorti U.,Search for Extraterrestrial Intelligence Institute | Gorti U.,NASA | And 7 more authors.
Astrophysical Journal | Year: 2015

We have used the Submillimeter Array to image, at ∼1.″5 resolution, C2H emission from the circumstellar disk orbiting the nearby (D = 54 pc), ∼8 Myr-old, ∼0.8 classical T Tauri star TW Hya. The SMA imaging reveals that the C2H emission exhibits a ring-like morphology. Based on a model in which the C2H column density follows a truncated radial power-law distribution, we find that the inner edge of the ring lies at ∼45 AU, and that the ring extends to at least ∼120 AU. Comparison with previous (single-dish) observations of C2H emission indicates that the C2H molecules are subthermally excited and, hence, that the emission arises from the relatively warm ( K), tenuous ( cm-3) upper atmosphere of the disk. Based on these results and comparisons of the SMA C2H map with previous submillimeter and scattered-light imaging, we propose that the C2H emission most likely traces particularly efficient photo-destruction of small grains and/or photodesorption and photodissociation of hydrocarbons derived from grain ice mantles in the surface layers of the outer disk. The presence of a C2H ring in the TW Hya disk hence likely serves as a marker of dust grain processing and radial and vertical grain size segregation within the disk. © 2015. The American Astronomical Society. All rights reserved.


Mzinyane T.D.,University of KwaZulu - Natal | Van Aardt J.,Chester rlson Center For Imaging Science | Ahmed F.,University of South Africa
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | Year: 2015

This study assessed the suitability of chlorophyll, nitrogen, and water content, derived from leaf-level spectroradiometer data, for estimating volume of Eucalyptus clones in KwaZulu-Natal, South Africa. Volume was derived from field measurements of diameter at breast height (dbh) and tree height. Chlorophyll, nitrogen, and water related indices were used to estimate merchantable volume of Eucalyptus clones. Analysis of variance (ANOVA) was used to assess whether significant differences could be detected amongst index values within the plots or compartments, based on different age groups, clones, and site qualities. Cross validation and model selection based on adjusted R2 and low Mallows' Cp were utilized in the development of volume models. The strength of the correlations for all clones combined was found to be much lower than the individual relationships for E. grandis and E. saligna. ANOVA results indicated that volume was significantly (P < 0.05) influenced by age, site quality, and the clone in question. Models developed using stepwise approach without ancillary data, such as age and site index, had low adjusted R2 values (0.47 ≥ R2 ≥ 0.72) and high root-mean-square error (RMSE) values compared to models that included ancillary data (0.81 ≥ R2 ≥ 0.90). Partial least square regression models exhibited higher R2(0.92 ≥ R2 ≥ 0.96) and lower RMSE and Mallows' Cp. These results suggest that spectral measurements of chlorophyll, nitrogen, and water content have potential as independent variables to assist in the estimation of merchantable volume of Eucalyptus clones. This has important implications since results can be extended to airborne data and regional assessments. © 2015 IEEE.


Williams M.D.,Chester rlson Center For Imaging Science | Van Aardt J.,Chester rlson Center For Imaging Science | Kerekes J.P.,Chester rlson Center For Imaging Science
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

Exploitation of imaging spectroscopy (hyperspectral) data using classification and spectral unmixing algorithms is a major research area in remote sensing, with reference data required to assess algorithm performance. However, we are limited by our inability to generate rapid, accurate, and consistent reference data, thus making quantitative algorithm analysis difficult. As a result, many investigators present either limited quantitative results, use synthetic imagery, or provide qualitative results using real imagery. Existing reference data typically classify large swaths of imagery pixel-by-pixel, per cover type. While this type of mapping provides a first order understanding of scene composition, it is not detailed enough to include complexities such as mixed pixels, intra-end-member variability, and scene anomalies. The creation of more detailed ground reference data based on field work, on the other hand, is complicated by the spatial scale of common hyperspectral data sets. This research presents a solution to this challenge via classification of low altitude, high spatial resolution (1m GSD) National Ecological Observatory Network (NEON) hyperspectral imagery, on a pixel-by-pixel basis, to produce sub-pixel reference data for high altitude, lower spatial resolution (15m GSD) AVIRIS imagery. This classification is performed using traditional classification techniques, augmented by (0.3m GSD) NEON RGB data. This paper provides a methodology for generating large scale, sub-pixel reference data for AVIRIS imagery using NEON imagery. It also addresses challenges related to the fusion of multiple remote sensing modalities (e.g., different sensors, sensor look angles, spatial registration, varying scene illumination, etc.). A new algorithm for spatial registration of hyperspectral imagery with disparate resolutions is presented. Several versions of reference data results are compared to each other and to direct spectral unmixing of AVIRIS data. Initial results are promising, with ground based surveying required to quantify the accuracy of emotely sensed reference data. © 2016 SPIE.


Yang J.,Chester rlson Center For Imaging Science | Messinger D.W.,Chester rlson Center For Imaging Science | Mathew J.J.,Chester rlson Center For Imaging Science | Dube R.R.,Chester rlson Center For Imaging Science
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

Blood stains are among the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Early detection of blood stains is particularly important since the blood reacts physically and chemically with air and materials over time. Accurate identification of blood remnants, including regions that might have been intentionally cleaned, is an important aspect of forensic investigation. Hyperspectral imaging might be a potential method to detect blood stains because it is non-contact and provides substantial spectral information that can be used to identify regions in a scene with trace amounts of blood. The potential complexity of scenes in which such vast violence occurs can be high when the range of scene material types and conditions containing blood stains at a crime scene are considered. Some stains are hard to detect by the unaided eye, especially if a conscious effort to clean the scene has occurred (we refer to these as "latent" blood stains). In this paper we present the initial results of a study of the use of hyperspectral imaging algorithms for blood detection in complex scenes. We describe a hyperspectral imaging system which generates images covering 400 nm - 700 nm visible range with a spectral resolution of 10 nm. Three image sets of 31 wavelength bands were generated using this camera for a simulated indoor crime scene in which blood stains were placed on a T-shirt and walls. To detect blood stains in the scene, Principal Component Analysis (PCA), Subspace Reed Xiaoli Detection (SRXD), and Topological Anomaly Detection (TAD) algorithms were used. Comparison of the three hyperspectral image analysis techniques shows that TAD is most suitable for detecting blood stains and discovering latent blood stains. © 2016 SPIE.


Yang J.,Chester rlson Center For Imaging Science | Mathew J.J.,Chester rlson Center For Imaging Science | Dube R.R.,Chester rlson Center For Imaging Science | Messinger D.W.,Chester rlson Center For Imaging Science
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

Blood stains are one of the most important types of evidence for forensic investigation. They contain valuable DNA information, and the pattern of the stains can suggest specifics about the nature of the violence that transpired at the scene. Blood spectral signatures containing unique refilectance or absorption features are important both for forensic on-site investigation and laboratory testing. They can be used for target detection and identification applied to crime scene hyperspectral imagery, and also be utilized to analyze the spectral variation of blood on various backgrounds. Non-blood stains often mislead the detection and can generate false alarms at a real crime scene, especially for dark and red backgrounds. This paper measured the refilectance of liquid blood and 9 kinds of non-blood samples in the range of 350 nm - 2500 nm in various crime scene backgrounds, such as pure samples contained in petri dish with various thicknesses, mixed samples with different colors and materials of fabrics, and mixed samples with wood, all of which are examined to provide sub-visual evidence for detecting and recognizing blood from non-blood samples in a realistic crime scene. The spectral difference between blood and non-blood samples are examined and spectral features such as "peaks" and "depths" of refilectance are selected. Two blood stain detection methods are proposed in this paper. The first method uses index to denote the ratio of "depth" minus "peak" over"depth" add"peak" within a wavelength range of the refilectance spectrum. The second method uses relative band depth of the selected wavelength ranges of the refilectance spectrum. Results show that the index method is able to discriminate blood from non-blood samples in most tested crime scene backgrounds, but is not able to detect it from black felt. Whereas the relative band depth method is able to discriminate blood from non-blood samples on all of the tested background material types and colors. © 2016 SPIE.

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