尹丽华, 杭娟, 康亮, 刘士建. 基于联合相机路径的红外视频稳像算法[J]. 红外与激光工程, 2021, 50(6): 20200405. DOI: 10.3788/IRLA20200405
引用本文: 尹丽华, 杭娟, 康亮, 刘士建. 基于联合相机路径的红外视频稳像算法[J]. 红外与激光工程, 2021, 50(6): 20200405. DOI: 10.3788/IRLA20200405
Yin Lihua, Hang Juan, Kang Liang, Liu Shijian. Infrared video image stabilization algorithm based on joint camera path[J]. Infrared and Laser Engineering, 2021, 50(6): 20200405. DOI: 10.3788/IRLA20200405
Citation: Yin Lihua, Hang Juan, Kang Liang, Liu Shijian. Infrared video image stabilization algorithm based on joint camera path[J]. Infrared and Laser Engineering, 2021, 50(6): 20200405. DOI: 10.3788/IRLA20200405

基于联合相机路径的红外视频稳像算法

Infrared video image stabilization algorithm based on joint camera path

  • 摘要: 针对由于视差变化而导致的红外视频稳像技术难题,文中提出了一种基于联合相机路径的红外视频稳像算法,该算法主要包括:预处理、联合相机路径求解、多路径优化、运动补偿四个步骤。首先,要对红外图像进行直方图均衡化、特征点提取和匹配处理、预映射。接着,要将每帧图像分为m×n个网格单元,利用基于网格的映射运动表征,将每一帧中对应网格得到的局部单应性矩阵进行相乘得到联合相机路径。然后,对联合相机路径采用“多路径优化”策略进行平滑处理。最后,利用平滑后路径进行运动补偿稳定视频。实验结果表明,该方法能有效地处理由于视差而引起的非线性运动,相比传统的稳像算法效果更好,当特征点存在部分遮挡时,也能取得不错的稳像效果。

     

    Abstract: To solve the problem of infrared video image stabilization caused by parallax variation, the infrared video image stabilization algorithm based on joint camera path was proposed, which included four steps: preprocessing, joint camera path solving, multi-path optimization and motion compensation. Firstly, histogram equalization, feature point extraction, matching processing and pre-mapping were needed for infrared image. Then, each frame of image was divided into m×n grid cells, and local homography matrixs obtained from the corresponding grid in each frame were multiplied by the mapping motion representation based on the grid to obtain the joint camera path. Then, the path of the joint camera was smoothed by the strategy of ‘multi-path optimization’. Finally, the smooth path was used to stabilize the video. The experimental results show that this method can effectively deal with the nonlinear motion caused by parallax, which is better than the traditional image stabilization algorithm, and can achieve good image stabilization even when the feature points have partial occlusion.

     

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