基于网格运动统计的视频图像快速拼接算法

FAST VIDEO IMAGE STITCHING ALGORITHM BASED ON GRID MOTION STATISTICS

  • 摘要: 为解决视频拼接过程中配准效率低、实时性差的问题,提出基于网格运动统计的视频图像快速拼接算法。将改进的快速旋转不变性特征(Oriented FAST and Rotated BRIEF,ORB)和网格运动统计(Grid-based Motion Statistics,GMS)算法相结合,优化图像金字塔尺度空间结构,引入快速视网膜关键点算法对特征点进行二进制描述,并采用最佳缝合线和拉普拉斯融合算法对多路视频进行拼接。经实验结果分析,提高了视频拼接的鲁棒性和实时性。与传统算法相比,图像配准速度在亮度、旋转、尺度方面分别提高28.7%、35.2%、33.9%,准确率分别提升21.6%、10.6%、9.9%。

     

    Abstract: In order to solve the problems of low registration efficiency and poor real-time performance during video stitching, we propose a fast video image stitching algorithm based on grid motion statistics. The algorithm combined the improved Oriented FAST and Rotated BRIEF (ORB) and Grid-based Motion Statistics (GMS) algorithm, and optimized the pyramid scale spatial structure of the image, introduced the fast retinal keypoint algorithm to describe the binary feature points, and used the optimal suture line and Laplacian fusion algorithm to stitch the multi-channel video. Experimental results show that the algorithm improves the robustness and real-time performance of video stitching. Compared with the traditional algorithm, this algorithm improves the image registration speed by 28.7%, 35.2% and 33.9% in brightness, rotation and scale, and improves the accuracy by 21.6%, 10.6% and 9.9%, respectively.

     

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