Abstract
An image fusion algorithm, based upon spectral mixture analysis, is presented. The algorithm combines low spatial resolution multi/hyperspectral data with high spatial resolution sharpening image(s) to create high resolution material maps. Spectral (un)mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. The outputs of unmixing are endmember fraction images (material maps) at the spatial resolution of the multispectral system. This research includes developing an improved unmixing algorithm based upon stepwise regression. In the second stage of the process, the unmixing solution is sharpened with data from another sensor to generate high resolution material maps. Sharpening is implemented as a nonlinear optimization using the same type of model as unmixing. Quantifiable results are obtained through the use of synthetically generated imagery. Without synthetic images, a large amount of ground truth would be required in order to measure the accuracy of the material maps. Multiple band sharpening is easily accommodated by the algorithm, and the results are demonstrated at multiple scales. The analysis includes an examination of the effects of constraints and texture variation on the material maps. The results show stepwise unmixing is an improvement over traditional unmixing algorithms. The results also indicate sharpening improves the material maps. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.
Library of Congress Subject Headings
Image processing--Digital techniques; Geographic information systems--Digital techniques; Geophysics--Remote sensing; Computer algorithms
Publication Date
8-1-1996
Document Type
Dissertation
Student Type
Graduate
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
Advisor
Schott, John
Advisor/Committee Member
Rhody, Harvey
Advisor/Committee Member
Gray, Robert
Recommended Citation
Gross, Harry, "An Image fusion algorithm for spatially enhancing spectral mixture maps" (1996). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/3044
Campus
RIT – Main Campus
Comments
Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: TA1632 .G768 1996