基于改进代价计算和路径优化策略的匹配算法

Matching Algorithm Based on Improved Cost Calculation and Path Optimization Strategy

为提升半全局匹配(SGM)算法效率,提出一种基于改进匹配代价计算和路径优化策略的立体匹配算法。代价计算阶段,通过对角线取点方式对局部二值模式(LBP)算子进行优化,降低时间复杂度和数据规模;代价聚合阶段,根据聚合逻辑选择5个方向进行扫描线优化,结合灰度相似性约束和距离约束条件,对聚合路径进行自适应权重赋值;再通过赢者通吃(WTA)策略计算初始视差值,通过左右一致性检测和二次多项式插值算法对视差图作进一步优化。最后算法在Middlebury 2.0和3.0数据平台上进行匹配效率验证,实验结果表明,所提算法相比SGM算法在不损失匹配准确度的情况下,代价计算阶段用时减少63.1%,代价聚合阶段用时减少39.3%,算法整体效率提升54.2%,达到效率提升的目的。

To improve the efficiency of the semi-global matching(SGM)algorithm,a stereo matching algorithm based on better matching cost calculation and a path optimization strategy is proposed.In the cost calculation stage,the local binary patterns(LBP)operator was optimized by taking diagonal points to reduce time complexity and memory usage;in the cost aggregation stage,five directions were selected for scan line optimization according to the aggregation logic,combined with gray-scale similarity and distance constraint conditions to perform adaptive weight assignment;then the initial disparity value was calculated using the winner-takes-all(WTA)strategy,and the aggregation path was further optimized by the disparity map through left and right consistency detection and the quadratic polynomial interpolation algorithm.Finally,the algorithm’s matching efficiency was validated using the Middlebury 2.0 and 3.0 data platforms.The experimental results show that when compared with the SGM algorithm,the proposed algorithm reduces the time used in the cost calculation stage by 63.1%and that in the cost aggregation stage by 39.3%.When the matching accuracy is slightly improved,the overall efficiency of the algorithm is increased by 54.2%,achieving the goal of efficiency improvement.