Treffer: Tensor Product Formulation for Hilbert Space-Filling Curves

Title:
Tensor Product Formulation for Hilbert Space-Filling Curves
Source:
Journal of information science and engineering. 24(1):261-275
Publisher Information:
Taipei: Institute of Information Science, Academia sinica, 2008.
Publication Year:
2008
Physical Description:
print, 30 ref
Original Material:
INIST-CNRS
Document Type:
Fachzeitschrift Article
File Description:
text
Language:
English
Author Affiliations:
Department of Information Engineering and Computer Science Feng Chia University, Taichung, 407, Tawain, Province of China
Graduate Institute of Medical Informatics Taipei Medical University, Taipei, 110, Tawain, Province of China
ISSN:
1016-2364
Rights:
Copyright 2008 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.20029230
Database:
PASCAL Archive

Weitere Informationen

We present a tensor product formulation for Hilbert space-filling curves. Both recursive and iterative formulas are expressed in the paper. We view a Hilbert space-filling curve as a permutation which maps two-dimensional 2 x 2 data elements stored in the row major or column major order to the order of traversing a Hilbert curve. The tensor product formula of Hilbert space-filling curves uses several permutation operations: stride permutation, radix-2 Gray permutation, transposition, and anti-diagonal transposition. The iterative tensor product formula can be manipulated to obtain the inverse Hilbert permutation. Also, the formulas are directly translated into computer programs which can be used in various applications including image processing, VLSI component layout, and R-tree indexing, etc.