Polarimetric modeling of remotely sensed scenes in the thermal infrared

This dissertation develops a polarimetric thermal infrared (IR) framework within the Digital Image and Remote Sensing Image Generation (DIRSIG) software tool enabling users in the remote sensing community to conduct system level trades and phenomenology studies. To support polarized reflection and emission modeling within DIRSIG, a generalized bi-directional reflectance distribution function (BRDF) is presented. This generalized form is a 4x4 element Mueller matrix that may be configured to resemble the commonly utilized Beard-Maxwell or Priest-Germer BRDF models. A polarized emissivity model is derived that leverages a hemispherical integration of the polarized BRDF and Kirchoff\u27s Law. A portable experimental technique for measuring polarized long-wave IR emissivity is described. Experimental results for sixteen target and background materials are fit to the polarized emissivity model. The resulting model fit parameters are ingested by DIRSIG to simulate polarized long-wave infrared scene phenomenology. Thermally emitted radiance typically has a vertical polarization orientation, while reflected background radiance is polarized horizontally. The balance between these components dictates what polarized signature (if any) is detected for a given target. In general, specular targets have a stronger emission polarization signature compared to diffusely scattering targets consistent with visible polarimetry findings. However, the influence of reflected background radiance can reduce the polarimetric signature of specular targets below a detectable threshold. In these situations, a diffusely scattering target may actually exhibit a polarization signature stronger than a specular target material. This interesting phenomenology is confirmed by experimental scene collections and DIRSIG simulations. Understanding polarimetric IR phenomenology with this level of detail is not only key for system design, but also for determining optimal collection geometries for specific tactical missions

On the Two q-Analogue Logarithmic Functions

There is a simple, multi-sheet Riemann surface associated with e_q(z)'s inverse function ln_q(w) for 0< q < 1. A principal sheet for ln_q(w) can be defined. However, the topology of the Riemann surface for ln_q(w) changes each time "q" increases above the collision point of a pair of the turning points of e_q(x). There is also a power series representation for ln_q(1+w). An infinite-product representation for e_q(z) is used to obtain the ordinary natural logarithm ln{e_q(z)} and the values of sum rules for the zeros "z_i" of e_q(z). For |z|<|z_1|, e_q(z)=exp{b(z)} where b(z) is a simple, explicit power series in terms of values of these sum rules. The values of the sum rules for the q-trigonometric functions, sin_q(z) and cos_q(z), are q-deformations of the usual Bernoulli numbers.Comment: This is the final version to appear in J.Phys.A: Math. & General. Some explict formulas added, and to update the reference

Synaptically-Competent Neurons Derived from Canine Embryonic Stem Cells by Lineage Selection with EGF and Noggin

Pluripotent stem cell lines have been generated in several domestic animal species; however, these lines traditionally show poor self-renewal and differentiation. Using canine embryonic stem cell (cESC) lines previously shown to have sufficient self-renewal capacity and potency, we generated and compared canine neural stem cell (cNSC) lines derived by lineage selection with epidermal growth factor (EGF) or Noggin along the neural default differentiation pathway, or by directed differentiation with retinoic acid (RA)-induced floating sphere assay. Lineage selection produced large populations of SOX2+ neural stem/progenitor cell populations and neuronal derivatives while directed differentiation produced few and improper neuronal derivatives. Primary canine neural lines were generated from fetal tissue and used as a positive control for differentiation and electrophysiology. Differentiation of EGF- and Noggin-directed cNSC lines in N2B27 with low-dose growth factors (BDNF/NT-3 or PDGFαα) produced phenotypes equivalent to primary canine neural cells including 3CB2+ radial progenitors, MOSP+ glia restricted precursors, VIM+/GFAP+ astrocytes, and TUBB3+/MAP2+/NFH+/SYN+ neurons. Conversely, induction with RA and neuronal differentiation produced inadequate putative neurons for further study, even though appropriate neuronal gene expression profiles were observed by RT-PCR (including Nestin, TUBB3, PSD95, STX1A, SYNPR, MAP2). Co-culture of cESC-derived neurons with primary canine fetal cells on canine astrocytes was used to test functional maturity of putative neurons. Canine ESC-derived neurons received functional GABAA- and AMPA-receptor mediated synaptic input, but only when co-cultured with primary neurons. This study presents established neural stem/progenitor cell populations and functional neural derivatives in the dog, providing the proof-of-concept required to translate stem cell transplantation strategies into a clinically relevant animal model

Evaluation of the Suitability of Polarimetric Scattering and Emissivity Models with Scene Generation Software

Software based polarimetric image generation models and hardware based infrared scene projectors commonly utilize analytical forms of polarized bi-directional reflectance distribution function and emission models. Many of these models are based in first principles physical concepts, but in practice are configured as least error fits to measured signatures. The resulting analytical model may well describe the lab measured data points, but provide erroneous results when integrated into a wide ranging radiometric simulation environment. In this work we present a methodology for characterizing the suitability of incorporating limited range lab measured data, usually through fitting to an analytical model, into a wider range modeling environment. We have found lab measured reflectance data can be fit to analytical models with parameters straying significantly from the first principles physical description of the surface. This effect may be due to over parameterization or an under sampled measurement space, resulting in radiometric anomalies when integrated into a larger scale, multi-surface, multi-material, modeling environment. Our methodology consists of a series of sanity tests that each scattering and emission model configuration must pass before confidence is had in the polarimetric optical property description