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An adaptive cost aggregation method based on bilateral filter and canny edge detector with segmented area for stereo matching
Author(s): Wei-Jong Yang; Zi-Shiung Tsai; Pau-Choo Chung ; Yao-Teng Cheng
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Paper Abstract

In traditional stereo matching, global approach is more accurate but time consuming, also have high accuracy in occlusion area. On the contrary, local approach is usually fast but have bad performance, and easily influenced by noise. This paper proposed a novel method to compute disparity between two images. It is based on local approach, but our new cost function aggregated the cost in global way. This aggregation is processed by a weight map which created by the bilateral filter. Every pixel transfers its own cost information to all pixels on the same object, but this information would be restricted by the weight map. After finishing preliminary depth map, we use L-R check to find occlusion and mismatch pixels to refined our depth map. These refinement mechanics fix occlusion areas by the smallest disparity nearby. At last, we use bilateral filter clean up whole depth map. All of above computing process can be parallelized on GPU or cloud sever. Although this algorithm is designed for lowlevel machine, it still exerts high performance in high-level hardware.

Paper Details

Date Published: 22 March 2019
PDF: 6 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110491J (22 March 2019); doi: 10.1117/12.2521396
Show Author Affiliations
Wei-Jong Yang, National Cheng Kung Univ. (Taiwan)
Zi-Shiung Tsai, National Cheng Kung Univ. (Taiwan)
Pau-Choo Chung , National Cheng Kung Univ. (Taiwan)
Yao-Teng Cheng, National Cheng Kung Univ. (Taiwan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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