Abstract: To solve the problems of poor stitch quality caused by color inconsistency,distortion and artifacts in binocular image stitch,a large field binocular image stitch algorithm based on improved mesh optimization is proposed.Firstly,an improved mesh optimization method based on translation transformation and global alignment constraints is designed.By minimizing an objective function consisting of point-line alignment term,global alignment term and salient line preservation term,the optimal mesh vertex set is obtained,which achieves image registration while preserving the original shape and structure information.Secondly,an image fusion algorithm based on improved histogram matching and seam search is designed.The difference of brightness and hue in the overlapping area and the color cast phenomenon under large disparity are eliminated by improved histogram matching,and the seam search method based on human perception is used to obtain the weighted fusion after the suture line,which can effectively avoid the artifacts caused by using weighted fusion in the unaligned feature sparse area.Finally,the proposed algorithm is compared with four algorithms such as SPW,LPC,PSC and NOVATEK in 10 large-field scenes.The average registration error of the proposed algorithm is reduced by 28.1% and the average distortion error is reduced by 99.5% compared with the suboptimal algorithm.The results show that the proposed algorithm can not only effectively eliminate the hue difference between binocular images,but also suppress the projection distortion in the non-overlapping area of the target image and remove the artifacts in the overlapping area,which has obvious advantages.

Key words: Binocular vision, Grid optimization, Image registration, Image stitching, Color correction, Optimal seam search