融合树分割与侧窗技术的局部立体匹配算法
Local Side Window Algorithm with Tree Segmentation for Stereo Matching
张杨 1沈乾 2刘汉威 3宋波 4宋鹏1
作者信息
- 1. 南京邮电大学通达学院,江苏 扬州 225127
- 2. 乔治华盛顿大学工程与应用科学学院,美国 华盛顿 20052
- 3. 江西机电职业技术学院电气工程系,江西 南昌 330013
- 4. 南京邮电大学现代邮政学院,江苏 南京 210003
- 折叠
摘要
针对当前局部立体匹配算法在边缘区域视差估计不准确的问题,提出一种融合树分割与侧窗技术的局部立体匹配算法.相较于传统局部立体匹配算法采用的固定窗口聚合策略,开发了一种基于侧窗技术的代价聚合策略,通过自适应选择最优侧窗来进行代价聚合,显著提高了边缘区域的视差精度.此外,在视差细化阶段引入树分割技术,并利用环形搜索传播可靠像素点,进一步提高边缘和复杂纹理区域的整体视差精度.在Middlebury数据集上的实验结果表明,所提算法在视差估计方面具有较高的视差计算精度和效率,特别是在图像边缘和复杂纹理等困难区域表现出良好的性能.
Abstract
We propose a local stereo matching algorithm that integrates tree segmentation with side window technology to enhance disparity estimation accuracy at edge regions,which is a common issue in existing local stereo matching algorithms.Unlike the traditional fixed window aggregation strategy,the proposed algorithm utilizes a cost aggregation strategy based on side window technology.This approach adaptively selects the optimal side window for cost aggregation,substantially improving the disparity accuracy in edge regions.Moreover,tree segmentation technology is employed during the disparity refinement stage to propagate reliable pixel points through circular searches,thereby enhancing disparity accuracy across edges and complex textured areas.Experimental results from the Middlebury dataset demonstrate that proposed algorithm achieves high accuracy and efficiency in disparity calculation,particularly excelling in challenging areas such as image edges and complex textures.
关键词
立体匹配/局部立体匹配/树分割/侧窗技术/边缘保护Key words
stereo matching/local stereo matching/tree segmentation/side window technology/edge protection引用本文复制引用
出版年
2024
NETL
NSTL
万方数据