An ikonos image fusion process using support value transform

Sheng Zheng, Wenzhong Shi, Jian Liu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Panehromatic (Pan)-sharpening of muttispectral (MS) bands is an important technique in various applications of satellite remote sensing. In this paper, we apply the support value transform (SVT) to lkonos image fusion. The fused saliency features are represented by support values and extracted by SVT. The low-resolution MS bands are resampled to the fine scale of the Pan image and sharpened by injecting the detailed features extracted from the high-resolution Pan image. The fusing results on Ikonos MS + Pan data demonstrate that the proposed image fusion method is effective and efficient.
Original languageEnglish
Title of host publicationProceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007
Pages1584-1589
Number of pages6
Volume3
DOIs
Publication statusPublished - 1 Dec 2007
Event6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 - Hong Kong, Hong Kong
Duration: 19 Aug 200722 Aug 2007

Conference

Conference6th International Conference on Machine Learning and Cybernetics, ICMLC 2007
Country/TerritoryHong Kong
CityHong Kong
Period19/08/0722/08/07

Keywords

  • Ikonos image fusion
  • Mapped least squares support vector machine (mapped LS-SVM)
  • Support value transform (SVT)

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Software
  • Theoretical Computer Science

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