H. S. Sidhu, Satish Kumar, Amitava Das, H. K. Sardana
{"title":"A robust area based disparity estimation technique for stereo vision applications","authors":"H. S. Sidhu, Satish Kumar, Amitava Das, H. K. Sardana","doi":"10.1109/ICIIP.2011.6108958","DOIUrl":null,"url":null,"abstract":"A novel and efficient stereo matching algorithm based on robust disparity estimation even in the presence of occlusions is presented in this paper. The algorithm employs the Sum of Absolute Difference (SAD) approach for measure of similarity between two images. A pre-processing stage is applied to smoothen the sharp changes in pixel values at the object boundaries and also help in reducing photometric distortion and noise. Occlusions are removed by using Left-Right consistency constraint which will be explained further in this paper. After the calculation of disparity, image information is combined with the pixel disparities to obtain a cleaner disparity map. The developed algorithm was tested on benchmarked Middlebury data sets as well as acquired sample images. The results obtained are in line with the results of the ground truth images.","PeriodicalId":201779,"journal":{"name":"2011 International Conference on Image Information Processing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 International Conference on Image Information Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIIP.2011.6108958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
A novel and efficient stereo matching algorithm based on robust disparity estimation even in the presence of occlusions is presented in this paper. The algorithm employs the Sum of Absolute Difference (SAD) approach for measure of similarity between two images. A pre-processing stage is applied to smoothen the sharp changes in pixel values at the object boundaries and also help in reducing photometric distortion and noise. Occlusions are removed by using Left-Right consistency constraint which will be explained further in this paper. After the calculation of disparity, image information is combined with the pixel disparities to obtain a cleaner disparity map. The developed algorithm was tested on benchmarked Middlebury data sets as well as acquired sample images. The results obtained are in line with the results of the ground truth images.
提出了一种基于鲁棒视差估计的立体匹配算法。该算法采用绝对差和(Sum of Absolute Difference, SAD)方法来度量两幅图像之间的相似性。预处理阶段用于平滑物体边界像素值的急剧变化,也有助于减少光度失真和噪声。使用左右一致性约束去除遮挡,本文将进一步解释。视差计算完成后,将图像信息与像素视差相结合,得到更清晰的视差图。开发的算法在基准Middlebury数据集以及获取的样本图像上进行了测试。所得结果与地面真值图像的结果一致。