A Markov random field-based approach to decision-level fusion for remote sensing image classification

Ryuei Nishii

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

A method is proposed for the enhancement of the quality of a classification result by fusing this result with remote sensing images, based on a Markov random field approach. The classification accuracy is estimated by a modified posterior probability, which is used for choosing the optimal classification result. The procedure is applied to a benchmark dataset for discrimination provided by the IEEE Geoscience and Remote Sensing Society Data Fusion Committee, and it shows an excellent performance. The classified result won the competition of the data fusion contest 2001 held by the same committee.

Original languageEnglish
Pages (from-to)2316-2319
Number of pages4
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume41
Issue number10 PART I
DOIs
Publication statusPublished - Oct 1 2003
Externally publishedYes

Fingerprint

image classification
Image classification
remote sensing
Remote sensing
fusion
multisensor fusion
Data fusion
discrimination
augmentation
decision

All Science Journal Classification (ASJC) codes

  • Geochemistry and Petrology
  • Geophysics
  • Computers in Earth Sciences
  • Electrical and Electronic Engineering

Cite this

A Markov random field-based approach to decision-level fusion for remote sensing image classification. / Nishii, Ryuei.

In: IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, No. 10 PART I, 01.10.2003, p. 2316-2319.

Research output: Contribution to journalArticle

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