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Full-Text Articles in Engineering
An Iterative Approach To Multisensor Sea Ice Classification, David G. Long, Mark R. Drinkwater, Quinn P. Remund
An Iterative Approach To Multisensor Sea Ice Classification, David G. Long, Mark R. Drinkwater, Quinn P. Remund
Faculty Publications
Characterizing the variability in sea ice in the polar regions is fundamental to an understanding of global climate and the geophysical processes governing climate changes. Sea ice can be grouped into a number of general classes with different characteristics. Multisensor data from NSCAT, ERS-2, and SSM/I are reconstructed into enhanced resolution imagery for use in ice-type classification. The resulting twelve-dimensional data set is linearly transformed through principal component analysis to reduce data dimensionality and noise levels. An iterative statistical data segmentation algorithm is developed using maximum likelihood (ML) and maximum a posteriori (MAP) techniques. For a given ice type, the …
Neural Networks Versus Nonparametric Neighbor-Based Classifiers For Semisupervised Classification Of Landsat Thematic Mapper Imagery, Perry J. Hardin
Neural Networks Versus Nonparametric Neighbor-Based Classifiers For Semisupervised Classification Of Landsat Thematic Mapper Imagery, Perry J. Hardin
Faculty Publications
Semisupervised classification is one approach to converting multiband optical and infrared imagery into landcover maps. First, a sample of image pixels is extracted and clustered into several classes. The analyst next combines the clusters by hand to create a smaller set of groups that correspond to a useful landcover classification. The remaining image pixels are then assigned to one of the aggregated cluster groups by use of a per-pixel classifier. Since the cluster aggregation process frequently creates groups with multivariate shapes ill suited for parametric classifiers, there has been renewed interest in nonparametric methods for the task. This research reports …