Square to Hexagonal Lattice Conversion Based on One-Dimensional Interpolation

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

3 Citations (Scopus)

Abstract

This paper concerns the square lattice to hexago- nal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one- dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.
LanguageEnglish
Title of host publicationUnknown Host Publication
Pages1-6
Number of pages6
DOIs
Publication statusE-pub ahead of print - 19 Jan 2017
EventInternational Conference on Image Processing Theory, Tools and Applications - Oulu, Finland
Duration: 19 Jan 2017 → …

Conference

ConferenceInternational Conference on Image Processing Theory, Tools and Applications
Period19/01/17 → …

Fingerprint

Interpolation
Computational efficiency
Image processing
Sampling
Processing

Keywords

  • Square sampling
  • hexagonal sampling
  • lattice con- version
  • separable filtering

Cite this

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title = "Square to Hexagonal Lattice Conversion Based on One-Dimensional Interpolation",
abstract = "This paper concerns the square lattice to hexago- nal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one- dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.",
keywords = "Square sampling, hexagonal sampling, lattice con- version, separable filtering",
author = "Xiangguo Li and Bryan Gardiner and Sonya Coleman",
year = "2017",
month = "1",
day = "19",
doi = "10.1109/IPTA.2016.7821035",
language = "English",
isbn = "978-1-4673-8910-5",
pages = "1--6",
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}

Li, X, Gardiner, B & Coleman, S 2017, Square to Hexagonal Lattice Conversion Based on One-Dimensional Interpolation. in Unknown Host Publication. pp. 1-6, International Conference on Image Processing Theory, Tools and Applications, 19/01/17. https://doi.org/10.1109/IPTA.2016.7821035

Square to Hexagonal Lattice Conversion Based on One-Dimensional Interpolation. / Li, Xiangguo; Gardiner, Bryan; Coleman, Sonya.

Unknown Host Publication. 2017. p. 1-6.

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

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N2 - This paper concerns the square lattice to hexago- nal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one- dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.

AB - This paper concerns the square lattice to hexago- nal lattice conversion in practical hexagonal image processing, and presents a simplified conversion method that converts the common two-dimensional (2-D) interpolation approach to one- dimensional (1-D) interpolation. This paper is motivated by the sampling interval relationship between the square lattice and the hexagonal lattice, and assumes the 2-D interpolation kernel as separable, then changes the 2-D interpolation into successive 1-D interpolations, and finally reduces to the 1-D interpolation along the horizontal direction only. Compared with the common 2-D interpolation approach, the proposed simplified conversion method is more simple and more computationally efficient, and it is also more suitable for parallel processing. Finally, the experimental results verify the correctness as well as the computational efficiency.

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