Adaptive stereo matching for SPOT multi-spectral image pairs

A. J. Chen, C. H. Liu, Jiann-Yeou Rau, L. C. Chen

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

1 Citation (Scopus)

Abstract

The DTM derived by image matching delineates the canopy surface, rather than the ground surface, and is suitable for the radiometric correction for multispectral images. If a pair of multispectral images is available, the DTM may be automatically generated by image matching, the geometric/radiometric corrections may be performed in a selfsufficient environment. To fully utilize the complimentary information of multispectral images, a scheme for adaptively matching a pair of SPOT multispectral images is proposed. Before starting a matching procedure the raw images are transformed to the quasi-epipolar coordinate system. Based on the least squares matching, each of the three-band images is applied first for similarity assessment with its counterpart. Then the best match is selected among the three bands for each point of the stereopair. The best match is considered successful provided the correlation coefficient is larger than a threshold. In addition to matching the gray scale images, we also test the performance of matching first principal component (PC1) pairs. Experimental results indicate that the highest accuracy is reached when the adaptive scheme includes the PC1 matching.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsHeinrich Ebner, Christian Heipke, Konrad Eder
Pages98-103
Number of pages6
Publication statusPublished - 1994 Dec 1
EventISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision - Munich, Ger
Duration: 1994 Sep 51994 Sep 9

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2357
ISSN (Print)0277-786X

Other

OtherISPRS Commission III Symposium: Spatial Information from Digital Photogrammetry and Computer Vision
CityMunich, Ger
Period94-09-0594-09-09

All Science Journal Classification (ASJC) codes

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

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