基于稀疏图像序列的雕塑点自动云三维重构方法

3D reconstruction method of sculpture point automatic cloud based on sparse image sequence

为了提高对雕塑点稀疏图像的点云三维重建的分析能力,提出一种基于稀疏图像序列的雕塑点自动云三维重构方法,基于稀疏散乱点三维重建和锐化模板特征匹配方法进行图像三维重建。采用三维角点检测和边缘轮廓特征提取方法,进行雕塑点稀疏图像三维点云特征检测,对检测的雕塑点稀疏图像点云数据进行信息融合处理,采用梯度运算方法进行特征分解,实现对雕塑点稀疏图像的信息增强和融合滤波。结合局部均值降噪方法进行图像的提纯处理,提高雕塑点稀疏图像轮廓重建能力,采用锐化模板特征匹配和块分割技术,实现雕塑点自动云三维重构。仿真结果表明,采用该方法进行雕塑点自动云三维重构的准确性较高,图像匹配能力较好,且重构输出信噪比较高。

In order to improve the analysis ability of point cloud 3D reconstruction of sparsely sculptured image,an automatic 3D reconstruction of sculpture point cloud based on sparse image sequence is proposed.3D reconstruction based on sparse scattered points and sharpened template feature matching method,3D comer detection and edge contour feature extraction method are used to detect 3D point cloud features of sparse image of sculpture points.In this paper,the point cloud data of the sparsely detected sculpture image is processed by information fusion,and the feature decomposition is carried out by u-sing gradient operation method,which realizes the information enhancement and fusion filtering of the sparse image of the sculpture point.Combined with the method of local mean noise reduction,the image is purified and filtered to improve the ability of sparse image contour reconstruction of sculpture points.The techniques of sharpen template feature matching and block segmentation are adopted to realize the automatic 3D reconstruction of sculpture point cloud.The simulation results show that the proposed method has high accuracy,good image matching ability and high signal-to-noise ratio(SNR)of reconstruction output.