摘要
提出了一种新的井下图像跟踪算法图像相关算法与卡尔曼滤波器之间的信息进行融合·此算法基于贝叶斯规则,将一种常用的均方差图像相关算法和卡尔曼滤波器两者信息进行融合,得到一种新的成像跟踪算法·改进后的算法融合了MSD相关器和卡尔曼滤波器两者的信息,使得两者之间的信息反馈增强,提高了跟踪算法的性能和鲁棒性,大大减少了目标失锁的可能性·另外,改进后的算法还融合了噪声的统计性能,提高了对噪声的抑制能力·从理论计算和实验结果看,用这种算法获得的图像比一般相关算法获得的图像更具有真实性和准确性·
A new underground image tracking algorithm is developed by way of a fusion done between a commonly-used mean square image correlator and Karlman filter, based on Bayes rule. With the fusion of both the information from the MSD correlator and Karlman filter, the improved algorithm can enhance the information feedback between them and its tracking performance and robustness so as to minimize the out-of-control possibility. Furthermore, the improved algorithm also incorporate the statistical characteristics of noise to improve noise suppressibility. The theoretical and practical results show that the images acquired from the new algorithm are much more real and accurate than the correlative algorithms.
出处
《东北工学院学报》
EI
CSCD
北大核心
2004年第6期547-550,共4页
基金
国家自然科学基金资助项目(69873007)
