An adaptive cost aggregation method based on bilateral filter and Canny edge detector with segmented area for stereo matching

• Main Authors: Zi-shiungTsai, 蔡子雄
• Other Authors: Pau-Choo Chung
• Format: Others
• Language: en_US
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/38205098639933194582

碩士 === 國立成功大學 === 電腦與通信工程研究所 === 102 === In traditional stereo matching method, global method is more accurate but spending more time, and have more correct rate in occlusion area. On the contrary, local method is usually fast but have bad performance, and easily is influence by noise. This paper proposed a novel method to compute disparity between two images. It is based on local method, but its cost be aggregated in like-global way. This aggregation is processed by a weight map which created by bilateral filter concept. Every pixel transfer its own cost information to all pixels on the same object, but this information would be restricted by weight map. After finishing preliminary depth map, we use L-R check to find occlusion and mismatch pixel. Then fix occlusion 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 machine or cloud sever. Although this algorithm is designed for low-level machine, it still exerts high performance in the world of high-level hardware.