北京测绘2026，Vol.40Issue(5)：600-605,6.DOI:10.19580/j.cnki.1007-3000.2025060032
融合组合代价与树形聚合的鲁棒半全局匹配算法
Robust semi-global matching algorithm integrating combined cost and tree-based aggregation
摘要
Abstract
This paper addressed the limitations of traditional semi-global matching algorithms that rely on a single matching cost,particularly in complex scenes where high texture similarity,strong sensitivity to lighting,and significant radiometric differences can easily cause matching discrepancies.An improved approach was proposed,which constructed a composite matching cost function that integrates pixel grayscale sum of squares and mutual information to evaluate image similarity using dual criteria.Additionally,a tree-based cost aggregation method was introduced,utilizing a minimum spanning tree to search for the globally optimal path.Tests on standard datasets such as the Middlebury dataset demonstrated the significant advantages of the improved algorithm:compared to traditional single cost measures,the combined cost model reduced the average mismatch rate in areas with repetitive textures and improved the disparity estimation accuracy in scenarios with strong lighting changes.Experimental data confirmed that this optimization method,which merges multiple feature criteria with a tree-based aggregation strategy,effectively solves the adaptability problem of traditional single measures in complex imaging environments,providing a new technological path for stereo matching.关键词
匹配代价/代价聚合/相似度检测/最小生成树/半全局匹配算法Key words
matching cost/cost aggregation/similarity detection/minimum spanning tree/semi-global matching algorithm分类
天文与地球科学引用本文复制引用
赖玉莹..融合组合代价与树形聚合的鲁棒半全局匹配算法[J].北京测绘,2026,40(5):600-605,6.基金项目
江西省自然资源厅科技创新项目(ZRKJ20232526 （）
ZRKJ20232411) （）
江西省地质局科技研究项目(2022JXDZKJKY02). （2022JXDZKJKY02）
