立体视觉算法步骤-Matching cost computation（匹配代价计算）
一提到视觉算法的步骤，不得不提《A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms》这篇文章。
因为目前大多数提到这个步骤，都是引用了这边文章，因为是这篇文章首次提出了立体视觉的四个步骤。而且《Stereo Vision:Algorithms and Applications》也是按照这四个步骤作为逻辑路线进行讲解。因此，作为初学者，按照这个思路学习，应该是个不错的选择。
本文的目的是，对《Stereo Vision:Algorithms and Applications》这篇文章进行概括和总结，拟出一条线路，以免后期迷失在茫茫文献中。
大多数的立体视觉分为四步
- Pre-processing（预处理）
有时通过预处理策略来补偿测量的损失，参考文献包括：
采用高斯拉普拉斯滤波
41. T. Kanade, H. Kato, S. Kimura, A. Yoshida, and K. Oda, Development of a Video-Rate Stereo Machine International Robotics and Systems Conference (IROS '95), Human Robot Interaction and Cooperative Robots, 1995
在像素附近减少平均值计算
[42] O. Faugeras, B. Hotz, H. Mathieu, T. Viville, Z. Zhang, P. Fua, E. Thron, L. Moll, G. Berry, Real-time correlation-based stereo: Algorithm. Implementation and Applications, INRIA TR n. 2013, 1993
双边滤波
[16] A. Ansar, A. Castano, L. Matthies, Enhanced real-time stereo using bilateral filtering IEEE Conference on Computer Vision and Pattern Recognition 2004
- Matching cost computation（匹配代价计算）
这一步的意义是：衡量待匹配像素与候选像素的相关性，尽量减小代价，因为代价越小，相关性越大。
不相关性测量
27. S. Birchfield and C. Tomasi. A pixel dissimilarity measure that is insensitive to image sampling.IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(4):401-406, April 1998
归一化互相关
57. S. Mattoccia, F. Tombari, L. Di Stefano, Fast full-search equivalent template matching by Enhanced Bounded Correlation, IEEE Transactions on Image Processing, 17(4), pp 528-538, April 2008
零平均归一化互相关
[58] L. Di Stefano, S. Mattoccia, F. Tombari, ZNCC-based template matching using Bounded Partial Correlation Pattern Recognition Letters, 16(14), pp 2129-2134, October 2005
中值滤波
[59] F. Tombari, L. Di Stefano, S. Mattoccia, A. Galanti, Performance evaluation of robust matching measures 3rd International Conference on Computer Vision Theory and Applications (VISAPP 2008)
非参数
[60] R. Zabih, J John Woodll Non-parametric Local Transforms for Computing Visual Correspondence, ECCV 1994
[61]D. N. Bhat, S. K. Nayar, Ordinal measures for visual correspondence, CVPR 1996
相互信息
[30] H. Hirschmüller. Stereo vision in structured environments by consistent semi-global matching. CVPR 2006, PAMI 30(2):328-341, 2008