Multidimensional Analysis Method for NOAA AVHRR Images

Jun Ichi Kudoh, Yoshiaki Nemoto, Norio Shiratori, Seijiro Obata, Shoichi Noguchi

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

As a fundamental study of multiple image processing, the authors have developed a new technique for the analysis of multispectral remote sensing data. Though the basis of the authors' algorithm is similar to a histogram analysis, they have proposed a novel way of the representation of multidimensional image data, which facilitates a nonexpert to locate and assign different classes present in the data set. The authors' experimentation was done with NOAA satellite image data. The brightness of the received data from channels of different frequency bands are the different dimensions of the multispectral image. By using this method, the authors could successfully classify NOAA satellite data received from the northern part of Japan, and locate the plane areas as an exercise. The authors have quantitatively compared their result with official data. The authors' result was found to be only 1 percent in deviation with the official data.

Original languageEnglish
Pages (from-to)949-954
Number of pages6
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume32
Issue number4
DOIs
Publication statusPublished - 1994 Jul

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Earth and Planetary Sciences(all)

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