摘要
在倾斜摄影三维建模过程中,碎片化纹理装箱处理可以加速纹理映射的读写过程,减轻内存和磁盘存储压力,但常用的二维矩形纹理装箱方法空间利用率较低。文章提出一种基于二叉树结点数组优化的二维矩形装箱纹理优化算法,通过对二维矩形按照面积大小排序完成预处理,在当前矩形存入完毕后按照面积比最大的原则分割剩余空间,并优化表示剩余空间的二叉树结点数组;通过二维矩形纹理装箱实验测试并与其他方法做了对比分析。结果表明:对碎片化纹理按照面积大小排序预处理可使纹理合并的空间利用率提高约5%;按照面积比最大原则分割剩余空间可使空间利用率提升约1倍;所研优化方法可以提高约10%的空间利用率,并使纹理集文件大小缩小35%。此方法对于提高纹理集的空间利用率具有显著效果。
In the three-dimensional modeling process of oblique photography,fragmented texture boxing can enhance the efficiency of reading and writing of texture mapping and reduce the pressure of memory and disk storage.However,the commonly used two-dimensional rectangular texture boxing method has low space utilization.This paper presents a two-dimensional rectangle packing texture optimization algorithm based on binary tree node array optimization,completes the the preprocessing step by sorting the two-dimensional rectangles according to the area size,divides the remaining space according to the principle of maximum area ratio after the current rectangle is stored,and optimizes the binary tree node array representing the remaining space.This paper also uses rectangular texture boxing experiment to conduct the test comparing this approach with other methods.The results show that the rate of space utilization of texture merging can be increased 5%by sorting and preprocessing the fragmented textures according to area size;dividing the remaining space according to the principle of maximum area ratio can results in a nearly twofold increase in space utilization;The proposed optimization method can improve the space utilization by about 10%and reduce the file size of texture sets by 35%.This method has a significant effect on improving the spatial utilization of texture sets.
作者
马东岭
朱悦凯
李铭通
MA Dongling;ZHU Yuekai;LI Mingtong(School of Surveying and Geo-Informatics,Shandong Jianzhu University,Jinan 250101,China)
出处
《山东建筑大学学报》
2023年第4期84-92,共9页
Journal of Shandong Jianzhu University
基金
山东省自然科学基金项目(ZR2020MD025)
山东建筑大学博士科研基金项目(X21079Z)。
关键词
纹理优化
矩形装箱
二叉树
结点优化
空间利用率
texture optimization
rectangular packing
binary tree
node optimization
space utilization
