Multidimensional analysis method for NOAA AVHRR images

Jun ichi Kudoh, Goutam Chakravorty, Yoshiaki Nemoto, Norio Shiratori, Hiroshi Kawamura, Seijiro Obata, Shoichi Noguchi

    Research output: Contribution to journalArticlepeer-review

    4 Citations (Scopus)

    Abstract

    As a fundamental study of multiple image processing, we have developed a new technique for the analysis of multispectral remote sensing data. Though the basis of our algorithm is similar to a histogram analysis, we 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. Our experimentation was done with NOAA satellite image data. Here, the brightness of the received data from channels of different frequency bands are the different dimensions of the multispectral image. By using our method, we could successfully classify NOAA satellite data received from the northern part of Japan, and located the plane areas as an exercise. We quantitatively compared our result with official data and our 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

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

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