The Simplification Method Based on Error Entropy
School of Civil Engineer and Architecture, East China Jiaotong University, 808 Shuanggang Road, Nanchang 330013, China
Abstract Currently, using the point cloud simplification, it is hard to achieve high precision, superior simplification rate and high speed. This paper proposes an adaptive point cloud simplification algorithm. Firstly, we use the PCA to estimate the normal of each point and to compute the angle between the normal vector and the reference plane. The characteristics of the surface can be determined by the local entropy of normal vector angles. The superior results of simplification can be derived according to the different simplification rate, counter to the characteristics of the surface. The results show that the proposed approach can reach a balance in the simplification precision, simplification rate, and simplification speed.
Key words ：
error entropy
point cloud simplification
normal vector
simplification rate
Received: 27 October 2014
Published: 01 December 2015
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