Open AccessTwo‐step mutual information‐based stereo matching
Author(s) -
Heo Y.S.
Publication year - 2016
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2016.0838
Subject(s) - mutual information , computation , matching (statistics) , computer science , dynamic programming , artificial intelligence , 3 dimensional matching , algorithm , feature (linguistics) , pattern recognition (psychology) , computer vision , mathematics , blossom algorithm , statistics , linguistics , philosophy
A fast mutual information (MI) based stereo matching method is proposed that estimates the optimal intensity transfer function in a Bayesian framework. Previous MI‐based stereo matching methods require several iterations, where each iteration includes both data cost computation and global energy optimisation such as dynamic programming and graph‐cuts. These computations are redundant and time‐consuming. In this Letter, a fast two‐step MI‐based stereo matching method by combining local feature correspondences and global statistics constraints is proposed. Experimental results show that the method is fast, yet generates results comparable with the original MI‐based method.