Band selection for hyperspectral images using copulas-based mutual information

Xuexing Zeng, T. S. Durrani

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

2 Citations (Scopus)

Abstract

This paper explores a new measure for band selection of hyperspectral images using copulas-based mutual information. Mutual information offers a measure of the dependence between random variables, which can be used to select specific bands for the analysis of hyperspectral images. This is achieved by comparing mutual information values between the band images and a reference map. In this paper, copula density functions are exploited for the estimation of mutual information between the images. Due to the special relationship between copula density functions and joint probability density functions, copulas offer a natural and robust way for the estimation of the mutual information.
Original languageEnglish
Title of host publication Statistical Signal Processing, 2009. SSP '09. IEEE/SP 15th Workshop on
PublisherIEEE
Pages341-344
Number of pages3
ISBN (Print)978-1-4244-2709-3
DOIs
Publication statusPublished - 6 Oct 2009
Event15th IEEE International Statistical Signal Procecssing Workshop, Cardiff, Wales -
Duration: 1 Jan 1900 → …

Conference

Conference15th IEEE International Statistical Signal Procecssing Workshop, Cardiff, Wales
Period1/01/00 → …

Keywords

  • band selection
  • Copulas
  • hyperspectral image
  • mutual information
  • bandwidth
  • density functional theory
  • entropy
  • hyperspectral imaging
  • probability density function
  • random variables
  • hyperspectral sensors
  • image processing
  • infrared detectors
  • geophysical signal processing
  • remote sensing

Fingerprint Dive into the research topics of 'Band selection for hyperspectral images using copulas-based mutual information'. Together they form a unique fingerprint.

Cite this