@inproceedings{6cc951421a17449eb31acfe854b5b907,
title = "SGM-Based Disparity Estimation Under Radiometric Variations",
abstract = "The semi-global matching (SGM) performances excellent in stereo correspondence field, it reaches a good trade-off between correspondence accuracy and computational complexity. However, the performance of SGM is limited under radiometric variations, such as varying lighting and exposure conditions. In this paper, an improved SGM method is presented to remedy this problem. To eliminate the discrepancy of illumination between the stereo images, both histogram equalization and binary singleton expansion are adopted in pre-processing stage. The weighted median filter is adopted after conventional LRC in the disparity refinement stage to remove the outlier errors and preserve edges. The stereo images from the Middlebury benchmark are used in the experiment. The experimental result show that the average RMSE of the improved SGM method is 12.64\% lower than the raw SGM. The proposed method can effectively improve the accuracy of disparity map compared to the SGM algorithm.",
keywords = "Binary singleton expansion, Histogram equalization, Radiometric variations, Semi-global matching, Weighted median filter",
author = "Yuan, \{Wei Min\} and Tong, \{Xiao Yan\} and Bin Xiao",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Singapore Pte Ltd.; 14th Conference on Image and Graphics Technologies and Applications, IGTA 2019 ; Conference date: 19-04-2019 Through 20-04-2019",
year = "2019",
doi = "10.1007/978-981-13-9917-6\_37",
language = "英语",
isbn = "9789811399169",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "382--391",
editor = "Yongtian Wang and Qingmin Huang and Yuxin Peng",
booktitle = "Image and Graphics Technologies and Applications - 14th Conference on Image and Graphics Technologies and Applications, IGTA 2019, Revised Selected Papers",
address = "德国",
}