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一种改进的基于平面先验的多视图密集匹配算法

王延 张勇 周雪飞 陈小杜 邢占春

地理空间信息2026,Vol.24Issue(4):122-125,4.
地理空间信息2026,Vol.24Issue(4):122-125,4.DOI:10.3969/j.issn.1672-4623.2026.04.025

一种改进的基于平面先验的多视图密集匹配算法

Improved Multi-view Dense Matching Algorithm Based on Planar Prior

王延 1张勇 2周雪飞 3陈小杜 3邢占春1

作者信息

  • 1. 中国电科网络通信研究院(中国电子科技集团公司第五十四研究所),河北 石家庄 050050
  • 2. 梧州学院 电子与信息工程学院,广西 梧州 543003
  • 3. 武汉航天远景科技股份有限公司,湖北 武汉 430220
  • 折叠

摘要

Abstract

To address the issue of reduced model accuracy caused by the assumption of non-planar regions as planar regions during the construc-tion of a planar prior using the ACMP algorithm,we put forward an improved multi-view dense matching algorithm based on planar prior.Firstly,we used Canny operator to detect image edges,and used the detection results to remove non-weak texture regions.Then,we used the images that removed non-weak texture regions to construct a weak texture region planar prior model,and used this model to implement the ACMP algorithm based on planar prior.In the subsequent sampling calculation process of depth map fusion,we used the weak texture region planar prior model to oversample on weak texture regions and perform a small amount of sampling on non-weak texture regions,which could reduce the density of point clouds in planar regions while preserve more point clouds details in non-planar regions.Experimental results show that the number of point clouds in the planar region of experimental data has decreased by about 43.1%,whereas the number in the non-planar region has increased by about 65.5%.Compared with existing methods,the improved algorithm enriches the model details of non-weak texture regions and improves the integrity of point clouds.

关键词

多视图立体视觉/多视图密集匹配/ACMH/ACMP

Key words

multi-view stereo vision/multi-view dense matching/ACMH/ACMP

分类

天文与地球科学

引用本文复制引用

王延,张勇,周雪飞,陈小杜,邢占春..一种改进的基于平面先验的多视图密集匹配算法[J].地理空间信息,2026,24(4):122-125,4.

基金项目

梧州学院人才引进科研启动基金资助项目(WZUQDJJ43022). (WZUQDJJ43022)

地理空间信息

1672-4623

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