基于混合优化方法的立体匹配算法

为了改善线性生长算法获得视差图可靠性差的问题,提出了一种基于混合优化方法的立体匹配算法。该算法综合考虑了计算效率和图像可靠性,将视差匹配转换为多目标优化问题,通过提出的基于模拟退火的鸽群优化算法求解此优化问题,从而实现视差阈值的自适应调节,并获取相应的根点的最优视差值。所提出的混合优化方法较好地克服了局部寻优和全局寻优方法易受初值影响且收敛速度慢的缺点。此外,为了进一步提高视差图可靠性,利用滤波法去除不可靠的视差。仿真结果表明,该算法可以获得更多深度信息,提高了线性生长算法计算视差图的可靠性和鲁棒性。

Stereo matching algorithm based on hybrid optimization method

A stereo matching algorithm based on the hybrid optimization method is proposed to improve the low reliability of the disparity map obtained by the linear growth algorithm. Considering the calculation efficiency and the image reliability comprehensively, the proposed algorithm converts disparity matching into a multi-objective optimization problem. This optimization problem is solved by the pigeon-inspired optimization algorithm based on simulated annealing for realizing the adaptive adjustment of the disparity threshold and obtaining the optimal disparity value of the corresponding root point. The proposed hybrid optimization method overcomes the shortcomings of the local and the global optimization methods, which are vulnerable to initial values and have slow convergence. In addition, the filtering method is used to remove unreliable disparity for further improving the reliability of the disparity map. The simulation results show that the algorithm can get more depth informations, which enhances the reliability and the robustness of the disparity map calculated by the linear growth algorithm.