基于视差与灰度双层支持窗的立体匹配算法

doi:10.16180/j.cnki.issn1007-7820.2019.11.003

Abstract

Abstract:

Aiming at the problem that traditional local matching support window is difficult to use pixel information with long distance and gray distance, a stereoscopic matching algorithm using double layer support windows based on disparity map and RGB map was proposed in this study. The algorithm obtained the first layer disparity support window according to the disparity map, and obtained the gray scale similar sub-support window by matching the RGB color gray value of the reference picture in the disparity support window. The aggregation matching cost was optimized by class dynamic programming algorithm with parallax window, gray window and central pixel as optimized paths. Finally, the WTA strategy was used to select the best disparity, update all disparities and iteratively optimize the disparity map until convergence of the disparity map was achieved. After evaluation by the Middlebury platform, the average mismatch rate of the new algorithm was 5.15%.

Key words: the disparity map, the grey map, double layer support windows, dynamic programming, iterative

CLC Number:

TN911.73

LI Xiaolin,LI Wenguo,LI Hao. A Stereo Matching Using Double Layer Support Windows Based on RGB Map and Disparity Map[J].Electronic Science and Technology, 2019, 32(11): 12-18.

Figures/Tables 5

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Table 1

References 18

[1]	张力, 黄影平 . 实时双目立体视觉系统的实现[J]. 电子科技, 2016,29(3):68-70.
	Zhang Li, Huang Yingping . Implementation of real-time binocular stereo vision system[J]. Electronic Science and Technology, 2016,29(3):68-70.
[2]	Hosni A, Rhemann C, Bleyer M , et al. Fast cost-volume filtering for visual correspondence and beyond[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013,35(2):504-11. doi: 10.1109/TPAMI.2012.156
[3]	林川 . 基于新扫描策略的快速立体匹配算法[J]. 电子科技, 2011,24(8):12-15.
	Lin Chuan . Fast stereo matching algorithm based on new scanning strategy[J]. Electronic Science and Technology, 2011,24(8):12-15.
[4]	Kanade T, Okutomi M . A stereo matching algorithm with an adaptive window: Theory and experiment[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994,16(9):920-932.
[5]	Yoon K J, Kweon I S . Adaptive support-weight approach for correspondence search[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006,28(4):650-656.
[6]	Hirschmuller H . Stereo processing by semiglobal matching and mutual information[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2008,30(2):328-341.
[7]	Cheng F, Zhang H, Sun M , et al. Cross-trees, edge and superpixel priors-based cost aggregation for Stereo matching[J]. Pattern Recognition, 2015,48(7):2269-2278.
[8]	刘杰, 张建勋, 代煜 . 基于区域增长的稠密立体匹配[J]. 机器人, 2017,39(2):182-188.
	Liu Jie, Zhang Jianxun, Dai Yu . Dense stereo matching based on region growing[J]. Robot, 2017,39(2):182-188.
[9]	Min D, Lu J, Do M N . Joint histogram-based cost aggregation for stereo matching[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013,35(10):2539-2545. doi: 10.1109/TPAMI.2013.15
[10]	Wang L Q, Liu Z, Zhang Z H . Feature based stereo matching using two-step expansion[J].Mathematical Problems in Engineering 2014(14):452803-452809.
[11]	祝世平, 闫利那, 李政 . 基于改进Census 变换和动态规划的立体匹配算法[J]. 光学学报, 2016,36(4):0415001-415018.
	Zhu Shiping, Yan Lina, Li Zheng . Stereo Matching algorithm based on Improved census transform and dynamic programming[J]. Acta Optics Sin, 2016,36(4):0415001-0415018.
[12]	Scharstein D, Szeliski R . A taxonomy and evaluation of dense two-frame stereo correspondence algorithms[J]. International Journal of Computer Vision, 2002,47(1-3):7-42. doi: 10.1023/A:1014573219977
[13]	Taniai T, Matsushita Y, Naemura T. Graph cut based continuous stereo matching using locally shared labels [C].Columbus:IEEE Conference on Computer Vision and Pattern Recognition,IEEE Computer Society, 2014.
[14]	Yang Q. A non-local cost aggregation method for stereo matching [C]. Providence:Computer Vision and Pattern Recognition,IEEE, 2012.
[15]	Chang X, Zhou Z, Wang L, et al. Real-time accurate stereo matching using modified two-pass aggregation and winner-take-all guided dynamic programming [C]. Hangzhou:International Conference on 3D Imaging, Modeling, Processing,Visualization and Transmission, 2011.
[16]	Rhemann C, Hosni A, Bleyer M, et al. Fast cost-volume filtering for visual correspondence and beyond [C]. Colorado Springs:IEEE Conference on Computer Vision and Pattern Recognition, 2011.
[17]	Psota E T, Kowalczuk J, Carlson J , et al. A local iterative refinement method for adaptive support-weight stereo matching[C].Las Vegas:Proceedings of the International Conference on Image Processing, Computer Vision, and Pattern Recognition(IPCV) , 2011.
[18]	Wang L, Yang R. Global stereo matching leveraged by sparse ground control points [C]. Colorado Springs:IEEE Conference on Computer Vision and Pattern Recognition, 2011.

算法	Tsukuba			Venus			Teddy			Cones			Average Error
算法	n-occ	all	disc	n-occ	all	disc	n-occ	all	disc	n-occ	all	disc	Average Error
本文算法	1.29	1.78	6.99	0.26	0.45	2.38	5.42	10.49	15.02	2.34	8.63	6.77	5.15
CostFilter	1.51	1.85	7.61	0.20	0.39	2.42	6.16	11.80	16.00	2.71	8.24	7.66	5.55
MCT	1.41	1.74	6.86	0.27	0.38	3.04	5.94	11.40	14.90	2.64	7.86	7.37	5.31
GlobalGCP	0.87	2.54	4.69	0.46	0.53	2.22	6.44	11.50	16.20	3.59	9.49	8.90	5.60
CrossTrees+SP	1.68	1.99	7.82	0.22	0.32	2.84	6.23	11.70	14.80	2.52	7.71	7.50	5.44
HistoAggr2	1.93	2.30	6.39	0.16	0.46	2.22	5.88	11.30	14.70	2.41	7.78	6.89	5.20
IterAdaptWgt	0.85	1.28	4.59	0.35	0.86	4.53	7.60	14.50	17.30	3.20	9.36	8.49	6.08
TwoStep	2.91	3.68	13.30	0.27	0.45	2.63	7.42	12.60	18.00	4.09	10.10	10.30	7.14

A Stereo Matching Using Double Layer Support Windows Based on RGB Map and Disparity Map

RichHTML

PDF (PC)

Like

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 5

References 18

Related Articles 13

Metrics

Comments

Recommended 3

[1]	ZHANG Xueying,WU Xiaoting,Daniel Eiliote Mbanze,ZHOU Zhengwei. Research on Scheduling of Pumped Storage Cascade Reservoir Based on SEOA Algorithm [J]. Electronic Science and Technology, 2019, 32(7): 17-21.
[2]	ZHAO Wei,ZENG Guohui,HUANG Bo,ZHU Shuangxin,LIU Jin. 3D Space Path Planning Research Based on Improved Local Search Algorithm [J]. Electronic Science and Technology, 2019, 32(6): 58-63.
[3]	LI Ying, XU Boqing. An Iterative Image Reconstruction Algorithm based on Compressed Sensing [J]. , 2016, 29(11): 129-.
[4]	MO Lidong, XU Boqing. An Improved TV Image Reconstruction Algorithm [J]. , 2016, 29(10): 47-.
[5]	NIAN Lei, MAI Yunfei. A Profile Tolerance Measurement System Based on Machine Vision [J]. , 2016, 29(10): 104-.
[6]	LI Chao. Design and Realization of TPC Coding Based on FPGA [J]. , 2015, 28(5): 121-.
[7]	LIU Mengtao,JIN Xiaofeng,LIU Daoyu,LIANG Tiancai. Color Correction Technology for Banknote Image Based on Iterative algorithm [J]. , 2015, 28(12): 107-.
[8]	ZHANG Han,DIAO Ming. Research into Non-binary LDPC Decoding Performance Factors [J]. , 2013, 26(8): 130-.
[9]	WAN Zhongqi,LIU Guozhong. Image Optimization Based on Deconvolution in Frequency-domain Coherence Tomography [J]. , 2013, 26(3): 72-.
[10]	XEI Mengmeng,WANG Yongchao. Narrowband Interference Suppression Based on Complex Adaptive Notch Filter [J]. , 2013, 26(11): 99-.
[11]	WEN Hong-Hang, REN Xiao-Li, WEN Hong-Xiang. Matrix Representation of the River Crossing Problem and the Iterative Algorithm [J]. , 2012, 25(10): 101-.
[12]	GUO Feng, WANG Dao-Ping, HAN Ming. Algorithm for Image Interestring Point Detection Based on Improved SUSAN Operator [J]. , 2011, 24(9): 9-.
[13]	ZHANG Feifei,LIU Zongqi,WANG Miao. The Rational Distribution of Electric Power Resource Based on Dynamic Programming [J]. , 2011, 24(6): 69-.