摘要
针对树型滤波匹配算法只需颜色一个要素计算权重而引起的匹配错误,提出一种基于像素点分类和颜色分割的树型滤波局部立体匹配算法。首先,在计算初始匹配代价时,按照稳定度将像素点分类;其次根据参考图像的颜色信息将其建立为代价树,并在建树的过程中根据颜色分割约束获得颜色分割图像;利用颜色分割图像和像素点分类信息,改进代价树中各边的权值;最后执行树型滤波,并获得稠密的视差图,从而完成立体匹配。采用Middlebury数据集进行的实验结果表明,该算法相比传统的树型滤波算法,在各区域的精度上都有一定的提升。
Tree filter matching method will cause wrong matching results since it considers only one single component with color to obtain the weight of support region. This paper presents a local tree filter stereo matching method based on pixel classification and color segmentation. The pixels of an image are classified according to their stability during their initial matching cost computation phase. A tree structure based on color information of reference image is constructed, meanwhile, a segmented image with color segmentation constraint is generated. The weight value of each edge is improved by utilizing the information of segmented color image and classified pixels. Finally, the tree filter is executed and the dense disparity is achieved. The experimental results on Middlebury datasets show that our proposed method has higher accuracy than other original tree filter methods in each special region.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2017年第3期606-611,共6页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金面上项目(61471150)
科技部国际科技合作专项项目(2014DFA12040)
浙江省重点科技创新团队项目(2011R50009)
浙江省自然科学基金面上项目(LY13F020033)
关键词
颜色分割
像素点分类
立体匹配
树型滤波
image segmentation
pixel classification
stereo matching
tree filter
