Paper
22 March 2019 An adaptive cost aggregation method based on bilateral filter and canny edge detector with segmented area for stereo matching
Wei-Jong Yang, Zi-Shiung Tsai, Pau-Choo Chung , Yao-Teng Cheng
Author Affiliations +
Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 110491J (2019) https://doi.org/10.1117/12.2521396
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Wei-Jong Yang, Zi-Shiung Tsai, Pau-Choo Chung , and Yao-Teng Cheng "An adaptive cost aggregation method based on bilateral filter and canny edge detector with segmented area for stereo matching ", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 110491J (22 March 2019); https://doi.org/10.1117/12.2521396
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Cited by 2 scholarly publications.
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KEYWORDS
RGB color model

Algorithm development

Digital filtering

Sensors

3D image processing

Venus

Cameras

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