1 July 2003 Method of normal estimation based on approximation for visualization
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Abstract
A normal estimation algorithm for visualization is presented that approximates the density function in a local neighborhood with a second-degree polynomial function. The coefficients of the polynomial function can be solved by minimizing the error of the approximation. This method is tested in several volume data sets and comparisons with other methods are presented. It is demonstrated that this method is a fairly robust technique for noise-contained data and is preferable for most applications.
© (2003) Society of Photo-Optical Instrumentation Engineers (SPIE)
Di-hui Hong, Gang-min Ning, Ting Zhao, Mu Zhang, Xiaoxiang Zheng, "Method of normal estimation based on approximation for visualization," Journal of Electronic Imaging 12(3), (1 July 2003). https://doi.org/10.1117/1.1579698 . Submission:
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