Aiming at problem that current non-local stereo matching algorithm has high false matching rate due to the selection of fixed parameters under different texture images

a non-local stereo matching algorithm with adaptive parameter is proposed. Color difference and cost of horizontal and vertical gradient are normalized and fused through weighing. Then a logarithmic transformation is performed based on the fused cost

which improves the performance of single pixel matching cost in low texture area. The average chroma difference of the reference image is calculated in hue

saturation

value（ HSV） color space

and then adjust cost aggregation parameter adaptively.The final disparity map is obtained after disparity selection. The experimental result show that the average error of the algorithm is 7. 86 % on the Middlebury test platform after processing on 31 groups of stero images pair. The mismatching rate in low texture region is further reduced

and the generalization ability of proposed algorithm is much better.