dc.contributor.author	Carter, Duane B.	en
dc.contributor.committeechair	Campbell, James B. Jr.	en
dc.contributor.committeemember	Wynne, Randolph H.	en
dc.contributor.committeemember	Randolph, John	en
dc.contributor.department	Geography	en
dc.date.accessioned	2014-03-14T20:51:16Z	en
dc.date.adate	1998-04-24	en
dc.date.available	2014-03-14T20:51:16Z	en
dc.date.issued	1998-03-23	en
dc.date.rdate	1999-04-24	en
dc.date.sdate	1998-03-23	en
dc.description.abstract	In recent years, as the availability of remote sensing imagery of varying resolution has increased, merging images of differing spatial resolution has become a significant operation in the field of digital remote sensing. This practice, known as data fusion, is designed to enhance the spatial resolution of multispectral images by merging a relatively coarse-resolution image with a higher resolution panchromatic image of the same geographic area. This study examines properties of fused images and their ability to preserve the spectral integrity of the original image. It analyzes five current data fusion techniques for three complex scenes to assess their performance. The five data fusion models used include one spatial domain model (High-Pass Filter), two algebraic models (Multiplicative and Brovey Transform), and two spectral domain models (Principal Components Transform and Intensity-Hue-Saturation). SPOT data were chosen for both the panchromatic and multispectral data sets. These data sets were chosen for the high spatial resolution of the panchromatic (10 meters) data, the relatively high spectral resolution of the multispectral data, and the low spatial resolution ratio of two to one (2:1). After the application of the data fusion techniques, each merged image was analyzed statistically, graphically, and for increased photointerpretive potential as compared with the original multispectral images. While all of the data fusion models distorted the original multispectral imagery to an extent, both the Intensity-Hue-Saturation Model and the High-Pass Filter model maintained the original qualities of the multispectral imagery to an acceptable level. The High-Pass Filter model, designed to highlight the high frequency spatial information, provided the most noticeable increase in spatial resolution.	en
dc.description.degree	Master of Science	en
dc.identifier.other	etd-32198-21323	en
dc.identifier.sourceurl	http://scholar.lib.vt.edu/theses/available/etd-32198-21323/	en
dc.identifier.uri	http://hdl.handle.net/10919/36609	en
dc.publisher	Virginia Tech	en
dc.relation.haspart	Etd.pdf	en
dc.relation.haspart	Fig_1.pdf	en
dc.relation.haspart	Fig_2.pdf	en
dc.relation.haspart	Fig_3.pdf	en
dc.relation.haspart	Fig_4.pdf	en
dc.relation.haspart	Fig_5.pdf	en
dc.relation.haspart	Fig_6.pdf	en
dc.relation.haspart	Fig11.pdf	en
dc.relation.haspart	Fig12.pdf	en
dc.relation.haspart	Fig13.pdf	en
dc.relation.haspart	Fig14.pdf	en
dc.relation.haspart	Fig15.pdf	en
dc.relation.haspart	Fig16.pdf	en
dc.relation.haspart	Fig17.pdf	en
dc.relation.haspart	Fig18.pdf	en
dc.relation.haspart	Fig19.pdf	en
dc.relation.haspart	Fig20.pdf	en
dc.relation.haspart	Fig21.pdf	en
dc.relation.haspart	Fig22.pdf	en
dc.relation.haspart	Fig23.pdf	en
dc.relation.haspart	Fig24.pdf	en
dc.relation.haspart	Fig25.pdf	en
dc.relation.haspart	Fig29.pdf	en
dc.relation.haspart	Fig30.pdf	en
dc.relation.haspart	Fig31.pdf	en
dc.relation.haspart	Fig41.pdf	en
dc.rights	In Copyright	en
dc.rights.uri	http://rightsstatements.org/vocab/InC/1.0/	en
dc.subject	Data Fusion	en
dc.subject	Brovey Transform	en
dc.subject	High-Pass Filter	en
dc.subject	Intensity-Hue-Saturation	en
dc.subject	Multiplicative	en
dc.subject	Principal Components Transformation	en
dc.title	Analysis of Multiresolution Data fusion Techniques	en
dc.type	Thesis	en
thesis.degree.discipline	Geography	en
thesis.degree.grantor	Virginia Polytechnic Institute and State University	en
thesis.degree.level	masters	en
thesis.degree.name	Master of Science	en

Analysis of Multiresolution Data fusion Techniques

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