A Comparative Study for Orthogonal Subspace Projection and Constrained Energy Minimization

Abstract

In this letter, we conduct a comparative study and investigate the relationship between two well-known techniques in hyperspectral image detection and classification: orthogonal subspace projection (OSP) and constrained energy minimization (CEM). It is shown that they are closely related and essentially equivalent provided that the noise is white with large SNR. Based on this relationship, the performance of OSP can be improved via data-whitening and noise-whitening processes.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2003
Accession Number
ADA453412

Entities

People

  • Chein-i. Chang
  • Hsuan Ren
  • Qian Du

Organizations

  • University of Maryland, Baltimore

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Background Noise
  • Classification
  • Computer Science
  • Covariance
  • Detection
  • Detectors
  • Earth Sciences
  • Eigenvalues
  • Eigenvectors
  • Electrical Engineering
  • Engineering
  • False Alarms
  • Filters
  • Noise
  • Remote Sensing
  • Warning Systems
  • White Noise

Fields of Study

  • Engineering

Readers

  • Business Analytics
  • Image Processing and Computer Vision.
  • Operations Research