| 摘要: |
| 与传统的基于局部几何信号去噪方法不同,提出了一种基于非局部几何信号的点模型去噪算法.该算法通过双边滤波算子,计算出每个点的微分坐标信息作为“几何灰度值”;基于模型上每个点的邻域的微分信息进行相似性匹配计算,对点模型上的“几何灰度值”进行全局加权平均,获得该点最终的微分信号;最后重建出该点的几何信息.进一步,提出了基于混合树的加速方法,对具有相似特征的邻域进行聚类,减少了匹配的空间复杂度,提高了计算效率.实验结果表明,算法简单高效,获得了满意的去噪效果. |
| 关键词: 点模型 相似性匹配 微分信号 非局部去噪 |
| DOI： |
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| 基金项目:Supported by the the National Grand Fundamental Research 973 Program of China under Grant No.2002CB312101 (国家重点基础研究发展规划(973)) |
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| A Non-Local Signal Processing Approach for Filtering Point Set Surface |
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XIAO Chun-Xia,LI Hui,MIAO Yong-Wei,PENG Qun-Sheng
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| Abstract: |
| Different from previous local smoothing filters based on local geometry signal, a novel denoising technique based on a non-local averaging of geometry signal of all sampled points on the point set surface is proposed. By using the bilateral filtering operator, the differential signal for each discrete point is obtained. The final geometry information of sample point can be reconstructed as the averaged geometry gray level computed by the NL-means. The mixture tree is applied to accelerate the similarity matching computation, which makes the NL-means more efficient for dealing with large point set surface. Experimental results illustrate that the approach is efficient and satisfied. |
| Key words: point set surface similarity matching differential signal non-local denoising |
