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Exploiting Sparsity And Dictionary Learning To Efficiently Classify Materials In Hyperspectral Imagery, Andrew E. Pound
Exploiting Sparsity And Dictionary Learning To Efficiently Classify Materials In Hyperspectral Imagery, Andrew E. Pound
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Hyperspectral imaging (HSI) produces spatial images with pixels that, instead of consisting of three colors, consist of hundreds of spectral measurements. Because there are so many measurements for each pixel, analysis of HSI is difficult. Frequently, standard techniques are used to help make analysis more tractable by representing the HSI data in a different manner.
This research explores the utility of representing the HSI data in a learned dictionary basis for the express purpose of material identification and classification. Multiclass classification is performed on the transformed data using the RandomForests algorithm. Performance results are reported.
In addition to classification, single …