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| Rapid Surface Interpolation from Massive Scattered Data Using Compactly Supported Radial Basis Functions and Conjugate Gradient Method |
| Yu Qiu-ze; Cao Ju; Liu Jian; Tian Jin-wen |
| Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image processing & Intelligence Control Huazhong University of Science and Technology Wuhan 430074 China |
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Abstract A novel algorithm for rapid surface interpolation from massive scattered data using Compactly Supported Radial Basis Functions (CSRBF) and conjugate gradient method is presented in this paper, CSRBF is used because it can make the coefficient equations symmetric positive definite (spd), and very sparse. So there must be a solver and a smat 1 storage memory are needed. In solving the system equations, iterative method is used. The conjugate gradient method is used to solve the system equations, because the method converges in at most N steps for a symmetric positive definite N by TV matrix. Experimental results using massive scattered points demonstrate the algorithm is fast. The proposed algorithm is very appropriate for surface interpolation from massive scattered points.
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Received: 09 October 2003
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2005, Vol. 27 
