Joint spatial and spectral analysis for remote sensing image classification

Hao Zheng, Linlin Shen, Sen Jia

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

With the development of sensors, the spatial and spectral resolutions of remote sensing data are getting much higher, which presents new possibilities and challenges for pixel based material classification. When most of the methods available in literature extract features in spectrum domain for land material classification, the rich information contained in hyperspectral data is not fully used. As a result, the classification accuracies reported in literature are not satisfying. In this work, we aim to use joint spatial and spectral analysis technique to extract information about signal variances in space, spectrum and joint space-spectrum domain. The feature thus extracted can better represent the signal variances and can thus improve overall classification accuracy.

Original languageEnglish
Title of host publicationMIPPR 2011
Subtitle of host publicationMultispectral Image Acquisition, Processing, and Analysis
DOIs
Publication statusPublished - 2011
Externally publishedYes
EventMIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis - Guilin, China
Duration: 4 Nov 20116 Nov 2011

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8002
ISSN (Print)0277-786X

Conference

ConferenceMIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis
Country/TerritoryChina
CityGuilin
Period4/11/116/11/11

Keywords

  • Classification
  • Joint spatial and spectral analysis
  • Remote sensing image

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Joint spatial and spectral analysis for remote sensing image classification'. Together they form a unique fingerprint.

Cite this