ISOMAP for wavelet distribution based image classification

This project concerns the inclusion of the ISOMAP non-linear reduction algorithm into two existing hyperspectral image analysis techniques: texture classification by wavelet distribution based geodesic distance calculations, and endmember extraction for unmixing purposes. The former technique is recently developed at the Visionlab, where the latter will provide an entirely new approach to an existing problem.

Keywords:HYPERSPECTRAL DATA ANALYSIS, CLASSIFICATION, IMAGE ANALYSIS

Disciplines:Applied mathematics in specific fields, Computer architecture and networks, Distributed computing, Information sciences, Information systems, Programming languages, Scientific computing, Theoretical computer science, Visual computing, Other information and computing sciences, Classical physics, Elementary particle and high energy physics, Other physical sciences