Context Dependent Spectral Unmixing

Abstract

A hyperspectral unmixing algorithm that finds multiple sets of endmembers is proposed. The algorithm, called Context Dependent Spectral Unmixing (CDSU), is a local approach that adapts the unmixing to different regions of the spectral space. It is based on a novel function that combines context identifucation and unmixing. This joint objective function models contexts as compact clusters and uses the linear mixing model as the basis for unmixing.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2014
Accession Number
ADA625331

Entities

People

  • Hamdi Jenzri

Organizations

  • University of Louisville

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Change Detection
  • Climate Change
  • Computer Science
  • Convex Sets
  • Detection
  • Detectors
  • Dimensionality Reduction
  • Hyperspectral Imagery
  • Information Science
  • Machine Learning
  • Pattern Recognition
  • Phyllosilicates
  • Remote Sensing
  • Signal Processing
  • Two Dimensional
  • Warning Systems

Readers

  • Computer Networking
  • Image Processing and Computer Vision.

Technology Areas

  • Space