Stereo matching algorithm based on improved Census transform and feature fusion
Aiming at the problem of low matching precision of local stereo matching algorithm,a stereo matching algorithm based on improved Census transform and feature fusion is proposed.Firstly,the neighborhood pixel information of transformation window is used to replace the central pixel,which solves the problem of traditional Census transform being overly dependent on the center pixel of the window.Then,the color information and gradient information of the image are introduced to construct a fusion cost calculation function to improve the reliability of the initial matching cost.In order to establish the connection between domain pixels,the idea of one-way dynamic programming is introduced for cost aggregation.Finally,a parallax hole filling method based on eight directions is proposed to optimize the disparity map.Experimental results show that average mis-matching rate of the proposed algorithm is3.77% on the Middlebury dataset,which is superior to other improved Census transform methods and has higher matching precision.
万方数据
维普
