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. 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. 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. 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.