Stereo Matching Algorithm Based On Integration Of Multi-Measurement

DOI

10.2991/wartia-16.2016.302How to use a DOI?

Keywords

Stereo matching, DSM , Census transform

Abstract

This paper presents a new measure method of stereo matching algorithm, which is based on image structure and pixel’s feature, named CGDSM. The matching cost calculate step consist of three similarity measure factors: pixel gradient similarity measure factor, pixel feature similarity measure factor and image structural similarity measure factor. At the cost aggregate step we use adaptive window to aggregate which is based on Canny edge information. At the disparity calculate step we use WTA(winner takes all) algorithm to find the optimal disparity. At the disparity refine step we use LRC(left-right consistency) method to refine disparity. The new algorithm contain more similarity measure function from image gradient information to color domain feature information and then to the spatial structural information. Experiment shows that this algorithm enhance the accuracy of stereo matching algorithm.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qiang Wu
AU  - Yuxiang Li
AU  - Shinan Lang
PY  - 2016/05
DA  - 2016/05
TI  - Stereo Matching Algorithm Based On Integration Of Multi-Measurement
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1483
EP  - 1488
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.302
DO  - 10.2991/wartia-16.2016.302
ID  - Wu2016/05
ER  -