Browsing by Subject "hyperspectral"
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Item A Compressive Sensing Approach To Hyperspectral Image Classification(2019-01-01) Della Porta, Charles John; Chang, Chein-I; Computer Science and Electrical Engineering; Engineering, ElectricalHyperspectral imaging (HSI) technology has found success in a variety of applications; however, its use is often still limited due to size, weight and power (SWaP) constraints. In this dissertations, compressive sensing (CS) is proposed as an enabling technology to reduce the high spectral band count, through the creation of compressively-sensed bands (CSBs). A CS model based on the universality of random sensing is proposed for the analysis of hyperspectral classification in the compressed domain. Specifically, the utility of the support vector machine (SVM) in the compressed domain is evaluated through both mathematical analysis and empirical experimentation. This work shows that is indeed possible to achieve full band classification performance in the compressed domain. The experiments also demonstrate that the minimum number of CSBs is scene dependent, requiring additional algorithms to provide a full solution. Two supervised algorithms based on a feature selection framework are proposed for estimating the minimum lower bound on the required number of CSBs. The first algorithm is based on feature filtering techniques and the second algorithm is based on classifier wrapping. Finally, an unsupervised algorithm is presented, based on progressive band processing, that is able to adaptively determine the required number of CSBs in-situ. The contributions of this dissertations provide the fundamental foundation for compressed classification of hyperspectral images and identify several new opportunities for future research.Item kCARTA : A fast pseudo line-by-line radiative transfer algorithm with analytic Jacobians, fluxes, Non-Local Thermodynamic Equilibrium and scattering for the infrared(EGU, 2019-08-09) Machado, Sergio DeSouza; Strow, L. Larrabee; Motteler, Howard; Hannon, ScottA fast pseudo-monochromatic radiative transfer package using a Singular Value Decomposition (SVD) compressed atmospheric optical depth database has been developed, primarily for use with hyperspectral sounding instruments. The package has been tested extensively for clear sky radiative transfer cases, using field campaign data and satellite instrument data. The current database uses HITRAN 2016 line parameters and is primed for use in the spectral region spanning 605 cm−1 to 2830 cm−1(with a point spacing of 0.0025 cm−1), but can easily be extended to other regions. The clear sky radiative transfer model computes the background thermal radiation quickly and accurately using a layer-varying diffusivity angle at each spectral point; it takes less than 20 seconds (on a 2.8 GHz core using 4 threads) to complete a radiance calculation spanning the infrared. The code can also compute Non Local Thermodynamic Equilibrium effects for the 4 µm CO2 region, as well as analytic temperature, gas and surface jacobians. The package also includes flux and heating rate calculations, and an interface to a scattering model.Item Spectral calibration in hyperspectral sounders(Society of Photo-Optical Instrumentation Engineers (SPIE), 2009-08-21) Manning, Evan M.; Aumann, Hartmut H.; Deen, Robert G.; Jiang, Yibo; Strow, L. Larrabee; Hannon, Scott E.It is widely accepted that the knowledge of the frequencies of the spectral response functions (SRF) of the channels of hyperspectral sounders at the 10 parts per million (ppm) of frequency level is adequate for the retrieval of temperature and moisture profiles and data assimilation for weather forecasting. However, SI traceability and knowledge at the 1 ppm level and better are required to separate artifacts in the knowledge of the SRF due to orbital and seasonal instrument effects from diurnal and seasonal effects due to climate change. We use examples from AIRS to discuss a spectral calibration that uses the SI traceable upwelling radiance spectra to achieve an absolute accuracy of 0.5 ppm.