IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v41y2009i2p970-978.html
   My bibliography  Save this article

Probability- and curve-based fractal reconstruction on 2D DEM terrain profile

Author

Listed:
  • Lai, Fu-Jou
  • Huang, Yueh Min

Abstract

Data compression and reconstruction has been playing important roles in information science and engineering. As part of them, image compression and reconstruction that mainly deal with image data set reduction for storage or transmission and data set restoration with least loss is still a topic deserved a great deal of works to focus on. In this paper we propose a new scheme in comparison with the well-known Improved Douglas–Peucker (IDP) method to extract characteristic or feature points of two-dimensional digital elevation model (2D DEM) terrain profile to compress data set. As for reconstruction in use of fractal interpolation, we propose a probability-based method to speed up the fractal interpolation execution to a rate as high as triple or even ninefold of the regular. In addition, a curve-based method is proposed in the study to determine the vertical scaling factor that much affects the generation of the interpolated data points to significantly improve the reconstruction performance. Finally, an evaluation is made to show the advantage of employing the proposed new method to extract characteristic points associated with our novel fractal interpolation scheme.

Suggested Citation

  • Lai, Fu-Jou & Huang, Yueh Min, 2009. "Probability- and curve-based fractal reconstruction on 2D DEM terrain profile," Chaos, Solitons & Fractals, Elsevier, vol. 41(2), pages 970-978.
    • Handle: RePEc:eee:chsofr:v:41:y:2009:i:2:p:970-978
    DOI: 10.1016/j.chaos.2008.04.026
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077908001999
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2008.04.026?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chung, Kuo-Liang & Hsu, Chung-Hsiang, 2006. "Novel prediction- and subblock-based algorithm for fractal image compression," Chaos, Solitons & Fractals, Elsevier, vol. 29(1), pages 215-222.
    2. He, Chuan-jiang & Li, Gao-ping & Shen, Xiao-na, 2007. "Interpolation decoding method with variable parameters for fractal image compression," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1429-1439.
    3. Chen, Ching-Ju & Lee, Tzong-Yeang & Huang, Y.M. & Lai, Fu-Jou, 2009. "Extraction of characteristic points and its fractal reconstruction for terrain profile data," Chaos, Solitons & Fractals, Elsevier, vol. 39(4), pages 1732-1743.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lu, Jian & Ye, Zhongxing & Zou, Yuru & Ye, Ruisong, 2008. "An enhanced fractal image denoising algorithm," Chaos, Solitons & Fractals, Elsevier, vol. 38(4), pages 1054-1064.
    2. Huang, Y.M. & Chen, Ching-Ju, 2009. "3D Fractal reconstruction of terrain profile data based on digital elevation model," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1741-1749.
    3. Chen, Zuoping & Ye, Zhenglin & Wang, Shuxun & Peng, Guohua, 2009. "Image magnification based on similarity analogy," Chaos, Solitons & Fractals, Elsevier, vol. 40(5), pages 2370-2375.
    4. Zhou, Yi-Ming & Zhang, Chao & Zhang, Zeng-Ke, 2009. "An efficient fractal image coding algorithm using unified feature and DCT," Chaos, Solitons & Fractals, Elsevier, vol. 39(4), pages 1823-1830.
    5. Zhou, Yi-Ming & Zhang, Chao & Zhang, Zeng-Ke, 2008. "Fast hybrid fractal image compression using an image feature and neural network," Chaos, Solitons & Fractals, Elsevier, vol. 37(2), pages 623-631.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:41:y:2009:i:2:p:970-978. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.