Iterative Algorithms for Abundance Estimation on Unmixing of Hyperspectral Imagery

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" Iterative Algorithms for Abundance Estimation on Unmixing of Hyperspectral Imagery "

Document Type	:	Latin Dissertation
Language of Document	:	English
Record Number	:	151944
Doc. No	:	ET23736
Main Entry	:	amuel Rosario Torres
Title Proper	:	Iterative Algorithms for Abundance Estimation on Unmixing of Hyperspectral Imagery
Note	:	This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract	:	Hyperspectral sensors collect hundreds of narrow and contiguously spaced spectralbands of data organized in the so-called hyperspectral cube. The spatial resolution of mostHyperspectral Imagery (HSI) sensors own nowadays is larger than the size of the objectsbeing observed. Therefore, the measured spectral signature is a mixture of the signatures ofthe objects in the طeld of view of the sensor. The high spectral resolution can be used to de-compose the measured spectra into its constituents. This is the so-called unmixing problemin HSI. Spectral unmixing is the process by which the measured spectrum is decomposedinto a collection of constituent spectra, or endmembers, and a set of corresponding fractionsor abundances. Unmixing allows us to detect and classify subpixel objects by their con-tribution to the measured spectral signal. In this research, two new abundance estimationalgorithms based on a least distance least square problem and compare it with other ap-proaches presented in the literature were developed. Algorithm validation and comparisonare done with real and simulated HSI data. HSI Abundance Estimation Toolbox (HABET)was implemented in the ENVI/IDL environment. Application of the unmixing algorithmfor remote sensing of benthic habitats is presented..............-....,....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject	:	Electericl tess
	:	برق
electronic file name	:	TL46993.pdf
Title and statement of responsibility and	:	Iterative Algorithms for Abundance Estimation on Unmixing of Hyperspectral Imagery [Thesis]