Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 21 for “"Spectral Unmixing"”.
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Vegetation Reflectance Estimation Through Optimization of a Spectral Unmixing Model
… response, and photosynthetic properties. Hyperspectral cameras and compact spectrometers are common instruments used in agriculture research and field applications to capture the vegetation reflectance spectrum at the canopy scale (about one meter from top of the crop). Although hyperspectral …
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Manifold learning based spectral unmixing of hyperspectral remote sensing data
<p>Nonlinear mixing effects inherent in hyperspectral data are not properly represented in linear spectral unmixing models. Although direct nonlinear unmixing models provide capability to capture nonlinear phenomena, they are difficult to formulate and the results are not always generalizable. …
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Understanding Soil Carbon Signatures from Hyperspectral Reflectance Data using Spectral Unmixing
… Moreover, the recent advancement of hyperspectral imagers has significantly increased spectral resolution, allowing more granular information to be captured. These devices offer a potentially more accurate methodology to quantify and monitor soil properties globally. Nevertheless, there is …
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Spectrally Resolved Detector Arrays for Multiplexed Biomedical Fluorescence Imaging
… of filter-based imaging systems. Hyper and multispectral imaging facilitate the detection of both spatial and spectral information in a single data acquisition, however, instrumentation for spatiospectral data acquisition is typically complex, bulky and expensive. This thesis seeks to overcome …
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Shedding light on the molecular interactomes of fast, complex biological processes using multispectral imaging with uncompromised spatiotemporal resolution
… introduced by imaging several structures. Multispectral imaging appeared as a promising avenue towards this goal as it tackles issues associated with spectral overlap thereby affording the visualisation of many fluorophores within a sample. However, current methods of acquiring multispectral …
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Map-guided hyperspectral image superpixel segmentation using semi-supervised partial membership latent Dirichlet allocation
… because of the high dimensionality of hyperspectral imagery, these regular superpixel segmentation algorithms often do not perform well in hyperspectral imagery. Although there are some authors who have modified some regular superpixel segmentation algorithms to fit the hyperspectral image, …
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Multiplexed nanoparticle-based immunoassays
… single-welled multiplexed immunosorbent assays. Spectral unmixing was investigated using mixtures of fluorophores and cadmium selenide quantum dots. Mixtures of up to four dyes were separated quantitatively using least squares minimisation, with relative standard error ranging from 0.5 to 13 %. …
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Land Cover Quantification using Autoencoder based Unsupervised Deep Learning
… model for land cover quantification through hyperspectral unmixing using an unsupervised autoencoder. Land cover identification and classification is instrumental in urban planning, environmental monitoring and land management. With the technological advancements in remote sensing, hyperspectral …
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Multi-scale Studies of Microbial Mats and Biocrusts: Integrating Remote Sensing with Field Investigations in Antarctica's McMurdo Dry Valleys
… and nitrogen. In Chapter 3, I assessed the spectral detectability of patchy biocrusts using multispectral satellite imagery to examine the environments in which biocrusts occur, finding that spectral unmixing of satellite imagery can successfully detect the presence of biocrust and its …
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Chemical identification under a poisson model for Raman spectroscopy
… two common general detection approaches, the spectral unmixing approach and the generalized likelihood ratio test (GLRT). The MHD framework is applied naturally to both the detection of individual target chemicals and to the detection of chemicals from a given class. The common, yet vexing, …
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Analyzing variation in snow albedo across spatial scales of observation in the Alaskan boreal forest
… vegetation cover. To do so, we compare multispectral and hyperspectral remote sensing instrumentation across scales of observation from ground-based transects to airborne and satellite-based measurements. Using airborne data from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG), we …
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Advanced Techniques for Automatic Change Detection in Multitemporal Hyperspectral Images
… the new generation remote sensing satellite hyperspectral images provides an important data source for Earth Observation (EO). Hyperspectral images are characterized by a very detailed spectral sampling (i.e., very high spectral resolution) over a wide spectral wavelength range. This important …
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Thermoacoustic Imaging and Spectroscopy for Enhanced Cancer Diagnostics
… PA signal 18 dB. Furthermore, through the use of spectral unmixing algorithms, the relative concentrations of multiple endogenous and exogenous co-localized absorbers were reconstructed in tumor bearing mice. The concentration of Alexaflour647 was calculated to increase nearly 20 dB in the center …
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Algorithms for spectral and spatio-spectral feature selection and classification for tunable sensors : theory and application
… and test new customized algorithms for infrared spectral imaging and remote sensing of terrestrial features and objects, with particular focus on a general class of sensors with noisy and overlapping spectral bands. While the principal driver of this dissertation is the bias-tunable …
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Suitability of Aster and SRTM dems, and satellite imagery in detailed geomorphological mapping in Dzanani Area of Makhado Local Municipality, Limpopo Province, Republic of South Africa
Detailed geomorphological mapping is important for monitoring environmental phenomena, it is therefore crucial that the methods employed for mapping are accurate. The basis of remote sensing for geomorphological work is moving from the consideration of whether satellite data are accurate for …
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Clinical Translation of Optoacoustic Imaging in Breast Cancer
… between the use of single wavelengths, spectral unmixing, vascularity versus receptor status, heterogeneity of signal intensity in relation to tumour stage and grade. This chapter also discusses the potential and limitations of quantifying the optoacoustic signal and leads to the final …
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Discriminating and mapping soil variability with hyperspectral reflectance data.
… developing new mapping methodologies from hyperspectral remote sensing and reflectance spectroscopy. The spatially continuous and rich spectral information of hyperspectral data provides a powerful diagnostic tool for mapping and monitoring the earth’s surface materials. Similarly, reflectance …
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