基于灰度塔评分的匹配模型构建在无人机网络视频拼接中的应用

Application of matching model based on grayscale tower score in unmanned aerial vehicle network video stitching

对于复杂非配合情况下,视频拼接中特征匹配对的数目和特征匹配准确率无法同时达到后续稳像和拼接的要求这一问题,提出一种基于灰度塔对特征点进行评分后构建匹配模型来进行精准特征匹配的方法。首先,利用灰度级压缩后相近灰度级合并这一现象,建立灰度塔来实现对特征点的评分;而后,选取评分高的特征点建立基于位置信息的匹配模型;最后,依据匹配模型的定位进行区域分块匹配来避免全局特征点的干扰和大误差噪点匹配,选择误差最小的特征匹配对作为最终结果匹配对。另外,在运动的视频流中,可通过前后帧信息建立掩模进行区域特征提取,匹配模型也可选择性遗传给后帧以节约算法时间。实验结果表明,在运用了基于灰度塔评分的匹配模型后,特征匹配对准确率在95%左右。相同帧特征匹配对的数目相较于随机采样一致性有近10倍的提升,在兼顾匹配数目和匹配准确率的同时且无大误差匹配结果,对于环境和光照有较好的鲁棒性。

Concerning the problem that in complex and non-cooperative situations the number of matching feature pairs and the accuracy of feature matching results in video stitching can not meet the requirements of subsequent image stabilization and stitching at the same time, a method of constructing matching model to match features accurately after feature points being scored by grayscale tower was proposed. Firstly, the phenomenon that the similiar grayscales would merged together after grayscale compression was used to establish a grayscale tower to realize the scoring of feature points. Then, the feature points with high score were selected to establish the matching model based on position information. Finally, according to the positioning of the matching model, regional block matching was performed to avoid the influence of global feature point interference and large error noise matching, and the feature matching pair with the smallest error was selected as the final result of matching pair. In addition, in a motion video stream, regional feature extraction could be performed by using the information of previous and next frames to establish a mask, and the matching model could be selectively passed on to the next frame to save the computation time. The simulation results show that after using this matching model based on grayscale tower score, the feature matching accuracy is about 95% and the number of matching feature pairs of the same frame is nearly 10 times higher than that of the traditional method. The proposed method has good robustness to environment and illumination while guaranteeing the matching number and the matching accuracy without large error matching result.