多参数加权的无缝纹理映射算法

目的 针对基于图像3维重建中纹理映射存在缝隙的问题,提出一种多参数加权的无缝纹理映射算法。方法 算法根据图像的标定信息对三角格网进行聚类分割,将重建模型聚类成不同参考图像的网格贴片,并对贴片排序生成纹理图像,加权融合重建顶点的法线角度、图像视点、模型深度等信息生成纹理贴片像素,最后采用多分辨率分解融合技术消除纹理贴片缝隙,实现无缝的纹理映射。结果 对不同的测试数据进行了验证,本文算法在保持一定清晰度的前提下消除了纹理的缝隙,即使对于构网误差较大的区域也能得到较为满意的结果,同时本文算法支持大数据的3维纹理映射。结论 提出了一种无缝的纹理映射算法,算法通过构造一个平滑的加权方程融合多源信息消除纹理的接缝,实验结果表明了本文算法的有效性及实用性,得到了高保真的无缝纹理映射效果,可应用到城市级别的大场景3维重建领域。

Seamless texture mapping algorithm based on multi parameter weighted

Objective Image-based modeling as a rapid means to reconstruct 3D models has become increasingly popular and gained significant attention. It has been widely used in virtual reality, 3D printing, and digital city construction. High-quality texture mapping is needed to improve visual effect and practical value of the reconstructed object to achieve high-quality 3D visual effects. For a texture mapping, generating a texture image fully automatically, eliminating color differences of an image, and achieving 3D seamless texture mapping are difficult because calibration parameters are inaccurate, images from different viewpoints have different illumination and colors, and 3D digital model has some minor differences. In addition, image pixels are not strictly aligned with model vertex, and one vertex corresponds to pixels of multiple images. Therefore, a seamless texture mapping algorithm based on multiparameter weighted fusion is proposed in this paper. Method Clustering and segmentation of the triangular grids are conducted according to image calibration information. Reconstruction models are clustered into several grid patches of different reference images, which are sequenced to create a texture image. Pixels of the texture patches are generated by weighted fusion of the reconstructed vertex normal angles, image viewpoints, and model errors. Finally, multiresolution decomposition and fusion are conducted for the texture image by eliminating patch gaps to achieve seamless texture mapping. Unlike traditional methods, all visible image sets are considered in the algorithm, and the influence of images that slightly contribute to the overall texture pixel is reduced through a weighting process to eliminate texture gaps while still guaranteeing texture clarity. Result We use different test data to verify the method. Experiments show that the proposed algorithm is effective and practical in obtaining a HI-FI 3D texture mapping effect relative to traditional methods. It maintains texture clarity while eliminating seams. The method can obtain satisfactory result even if grid accuracy and image calibration are limited by properly dealing with lighting differences in between images. The proposed algorithm also supports 3D texture mapping of large data. Conclusion According to the demand for image 3D reconstruction, a seamless texture mapping algorithm based on multiparameter weighted fusion is proposed in this paper. The algorithm fully considered several factors, such as lighting differences, reconstruction accuracy, and limited calibration accuracy of the image. Moreover, texture gaps are eliminated by establishing a smooth weighting equation to fuse multisource information, thereby achieving seamless texture mapping while maintaining texture clarity. In addition, the algorithm can process large data and can be used in city-scale 3D reconstruction field.