English  |  正體中文  |  简体中文  |  Items with full text/Total items : 67621/67621 (100%)
Visitors : 23098672      Online Users : 83
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version


    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29231


    Title: WAVELET-BASED SHAPE FROM SHADING
    Authors: HSIEH,JW;LIAO,HYM;KO,MT;FAN,KC
    Contributors: 資訊工程研究所
    Keywords: ILLUMINANT DIRECTION;MULTIRESOLUTION;REPRESENTATIONS;DECOMPOSITION;EQUATIONS;TEXTURE
    Date: 1995
    Issue Date: 2010-06-29 20:17:01 (UTC+8)
    Publisher: 中央大學
    Abstract: This paper proposes a wavelet-based approach for solving the shape from shading (SFS) problem. The proposed method takes advantage of the nature of wavelet theory, which can be applied to efficiently and accurately represent ''things,'' to develop a faster algorithm for reconstructing better surfaces. To derive the algorithm, the formulation of Horn and Brooks ((Eds.) Shape from Shading, MIT Press, Cambridge, MA, 1989), which combines several constraints into an objective function, is adopted. In order to improve the robustness of the algorithm, two new constraints are introduced into the objective function to strengthen the relation between an estimated surface and its counterpart in the original image. Thus, solving the SFS problem becomes a constrained optimization process. Instead of solving the problem directly by using Euler equation or numerical techniques, the objective function is first converted into the wavelet format. Due to this format, the set of differential operators of different orders which is involved in the whole process can be approximated with connection coefficients of Daubechies bases. In each iteration of the optimization process, an appropriate step size which will result in maximum decrease of the objective function is determined. After finding correct iterative schemes, the solution of the SFS problem will finally be decided. Compared with conventional algorithms, the proposed scheme is a great improvement in the accuracy as well as the convergence speed of the SFS problem. Experimental results, using both synthetic and real images, prove that the proposed method is indeed better than traditional methods. (C) 1995 Academic Press, Inc.
    Relation: GRAPHICAL MODELS AND IMAGE PROCESSING
    Appears in Collections:[資訊工程研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML375View/Open


    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明