Registration and Reconstruction
Biorthogonal Wavelet Surface Reconstruction Using Partial Integrations
Xiaohua Ren, Luan Lyu, Xiaowei He, Wei Cao, Zhixin Yang,
Bin Sheng, Yanci Zhang, Enhua Wu,
Zhixin Yang
FST, University of Macau
State Key Lab. of Internet of Things for Smart City, Univ. of Macau
Search for more papers by this authorCorresponding Author
Enhua Wu
FST, University of Macau
State Key Lab. of CS, ISCAS & Univ. of CAS
Zhuhai-UM S&T Research Institute
[email protected]Search for more papers by this authorXiaohua Ren, Luan Lyu, Xiaowei He, Wei Cao, Zhixin Yang,
Bin Sheng, Yanci Zhang, Enhua Wu,
Zhixin Yang
FST, University of Macau
State Key Lab. of Internet of Things for Smart City, Univ. of Macau
Search for more papers by this authorCorresponding Author
Enhua Wu
FST, University of Macau
State Key Lab. of CS, ISCAS & Univ. of CAS
Zhuhai-UM S&T Research Institute
[email protected]Search for more papers by this authorAbstract
We introduce a new biorthogonal wavelet approach to creating a water-tight surface defined by an implicit function, from a finite set of oriented points. Our approach aims at addressing problems with previous wavelet methods which are not resilient to missing or nonuniformly sampled data. To address the problems, our approach has two key elements. First, by applying a three-dimensional partial integration, we derive a new integral formula to compute the wavelet coefficients without requiring the implicit function to be an indicator function. It can be shown that the previously used formula is a special case of our formula when the integrated function is an indicator function. Second, a simple yet general method is proposed to construct smooth wavelets with small support. With our method, a family of wavelets can be constructed with the same support size as previously used wavelets while having one more degree of continuity. Experiments show that our approach can robustly produce results comparable to those produced by the Fourier and Poisson methods, regardless of the input data being noisy, missing or nonuniform. Moreover, our approach does not need to compute global integrals or solve large linear systems.
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