Data fusion of multispectral remote sensing measurements using wavelet transform

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dc.contributor.advisor Dr. Hamid Krim, Committee Chair en_US
dc.contributor.advisor Dr. Marc Genton, Committee Member en_US
dc.contributor.advisor Dr. Brian Hughes, Committee Member en_US
dc.contributor.author Mehta, Viraj Kirankumar en_US
dc.date.accessioned 2010-04-02T17:59:42Z
dc.date.available 2010-04-02T17:59:42Z
dc.date.issued 2003-04-02 en_US
dc.identifier.other etd-03282003-133133 en_US
dc.identifier.uri http://www.lib.ncsu.edu/resolver/1840.16/953
dc.description.abstract This thesis focuses on fusion of multispectral data available from remote sensing instruments. The aim is to develop fast and memory efficient algorithms that may be used for real-time implementation aboard satellites. Multiple channel data from the SSM/I instrument are used for experiments. Starting with a Bayesian estimation formulation of the data fusion problem, an attempt is made to take advantage of the sparseness resulting from wavelet transforms to optimize computational efficiency. After generating the necessary statistical models for the data to be estimated, a preconditioning whitening filter, which simplifies the choice of the required wavelet transform, is developed. The significant gains obtained by a compact representation in wavelet basis are shown. An input grid transformation leading to channel filters is then used to construct a real-time implementation of the optimal estimator. Simulated results of such a system are then used to demonstrate the achieved improvement in field resolution. In conclusion, a direction for future work is laid out for improving the estimation optimality over non-stationarity by adaptive techniques and extension to future instruments. en_US
dc.rights I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to NC State University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. en_US
dc.subject bayesian estimation en_US
dc.subject wavelet transform en_US
dc.subject remote sensing en_US
dc.subject multispectral en_US
dc.subject Data fusion en_US
dc.title Data fusion of multispectral remote sensing measurements using wavelet transform en_US
dc.degree.name MS en_US
dc.degree.level thesis en_US
dc.degree.discipline Electrical Engineering en_US


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