Accession Number : ADA320415
Title : An Image Fusion Algorithm for Spatially Enhancing Spectral Mixture Maps.
Descriptive Note : Doctoral thesis,
Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH
Personal Author(s) : Gross, Harry N.
PDF Url : ADA320415
Report Date : 09 JAN 1997
Pagination or Media Count : 127
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.
Descriptors : *IMAGE PROCESSING, *DATA FUSION, ALGORITHMS, SPATIAL DISTRIBUTION, ACCURACY, THESES, NONLINEAR SYSTEMS, MIXING, MAPPING, PIXELS, SPECTRUM ANALYSIS, MULTISPECTRAL.
Subject Categories : Cybernetics
Distribution Statement : APPROVED FOR PUBLIC RELEASE