Interactive analysis method for multidimensional images using a Hilbert curve

Seiichiro Kamata, Eiji Kawaguchi, Michiharu Niimi

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

A new interactive method for classifying multispectral images using the Hilber curve is described. A one-to-one mapping from N-dimensional space to one-dimensional space, Hilbert curve allows the users to extract category clusters without computing any distance in N-dimensional space easily. The users can analyze multidimensional images hierarchically from gross data distribution to fine data distribution. To realize the real time response from the system, data tables storing the addresses and the occurrence of the data are used.

Original languageEnglish
Pages (from-to)83-92
Number of pages10
JournalSystems and Computers in Japan
Volume26
Issue number3
Publication statusPublished - 1995 Mar
Externally publishedYes

Fingerprint

Cluster computing
Hilbert spaces
Data Distribution
Hilbert
Cluster Category
Interactive Methods
Multispectral Images
Curve
Gross
Response Time
Tables
Hilbert space
Computing

ASJC Scopus subject areas

  • Hardware and Architecture
  • Information Systems
  • Theoretical Computer Science
  • Computational Theory and Mathematics

Cite this

Interactive analysis method for multidimensional images using a Hilbert curve. / Kamata, Seiichiro; Kawaguchi, Eiji; Niimi, Michiharu.

In: Systems and Computers in Japan, Vol. 26, No. 3, 03.1995, p. 83-92.

Research output: Contribution to journalArticle

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