TDICCD相机大视场多通道遥感图像自动拼接方法  

Automatic Mosaic Method of Large Field View and Multi-Channel Remote Sensing Images of TDICCD Cameras

作　　者：禄金波[1,2] 何斌[1] 

机构地区：[1]中国科学院长春光学精密机械与物理研究所,长春130033 [2]中国科学院研究生院,北京100049

出　　处：《空间科学学报》2012年第1期154-160,共7页Chinese Journal of Space Science

基　　金：国家高技术研究发展计划项目资助(863-2-5-1-13B)

摘　　要：在TDICCD大视场多通道遥感图像的拼接中,由于存在成像平台谐振及颤振等因素的影响,以往的经典方法抗噪性和鲁棒性不高,很难达到图像高精度和快速拼接的要求.为此,提出了一种空域互相关自校正亚像素配准方法.该方法针对TDICCD多通道图像间重叠像素的特点,采用变搜索窗口的互相关系数作为评价函数;采用局部检测法监视图像参数的变化,找出图像每一部分最佳参数;采用干扰点排除法控制图像中误匹配的点,使参数更加可信;在最佳点配准的基础上,采用所提出的亚像素定位法对配准进行补偿.实际遥感图像拼接结果征明,该算法精度优于0.1 pixel,同时比其他方法速度快,稳定性、抗噪性和鲁棒性都很高,拼接图像获得了良好的效果.In terms of mosaic of TDICCD large field view and multi-channel remote sensing images, noise immunity and robustness of the previous classical method is not high, which is difficult to achieve high accuracy and fast image mosaic because of imaging resonance, flutter and other factors in the imaging platforms. For that reason, this paper proposes a more appropriate method,namely the spatial cross-correlation self-tuning sub-pixel registration method. Firstly, because of the characteristics of overlapping pixels between TDICCD multi-channel images, the method uses the cross correlation of variable search window as the evaluation function. Secondly, the local detection method is employed to monitor change of parameter to figure out the best parameters of each part of images. Thirdly, the matching error points are controlled by interference elimination method, so that parameters are more credible. Finally, sub-pixel locating algorithm is proposed to reduce error of image registration. The results of practical remote sensing image mosaic indicate that accuracy of the algorithm excesses O.lpixel, while rapidity, stability, noise immunity and robustness are higher than other methods and image mosaic obtains expected results.

关 键 词：TDICCD 遥感图像 多通道 空域互相关 亚像素 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]