基于韦伯感知和导引滤波分层聚合快速立体图像匹配

Hierarchical Aggregation Fast Stereo Image Matching Based on Weber Perception and Guided Filtering

该文利用韦伯定律和导引滤波提出基于代价分层聚合的快速立体匹配方法。首先提取立体图像对各彩色通道Weber描述符并初始化匹配代价。利用导引滤波增强匹配代价并提取视差候选;利用候选子集联合空间离散采样与自适应支持权重实现分层代价聚合;据此快速择优选取初始视差。视差求精中采用改进型双边滤波和对称映射后处理有效改善初始视差图中歧义区域。实验表明,该文方法能有效消除匹配歧义,获得分段平滑、高精度稠密视差;结构简单、快速高效且对光照变化具有鲁棒性。

This paper presents a hierarchical cost aggregation-based fast stereo image matching method based on Weber＇s law and guided filtering.Weber local descriptors for each color channel are firstly extracted from stereo pairs,and raw matching costs between the images are initialized by the descriptors.The matching costs are enhanced with guided filtering to extract the subsets of disparity candidates.Joint spatial discrete sampling and adaptive support weight are utilized to implement hierarchical cost aggregation on the candidate subsets.Then initial disparities from the subsets are selected fast and optimally.Modified bilateral filtering and symmetric warping-based post-processing are sequentially exploited in disparity refining to improve effectively ambiguous regions of initial disparity maps.The experimental results indicate that this proposed technique can obtain piecewise smooth,accurate and dense disparity map while eliminating effectively matching ambiguity.Being concise,fast and high efficiency,and it is robust to illumination change.