Study on Instantaneous Imaging Model of Aerial Time Series Images

doi:10.13474/j.cnki.11-2246.2017.0374

Abstract

Abstract: Object in the object space is moving absolutely with the time. The differences of movement caused the changes of the relative position. Time series images recorded the dynamic changes of the object space. Based on the dynamic characteristics of time series images, this paper introduced the time element to the collinear equation and derived instantaneous imaging model of time series images in order to describe the dynamic relationship between the object space and image space. This paper established the application model which different dynamic object can extract the motion features or elevation information from the dynamic image characteristics. Through simulation and analysis of real aerial image sequences test, it is shown that the instantaneous imaging model of time series images proposed in this paper can quantitatively calculate the mapping relationship between the image and the object.

Key words: motion characteristics of time series images, instantaneous image model of aerial time series images, exposure time interval

CLC Number:

P237

GAO Li, LIU Zhi, JIANG Zhenzhi, ZHANG Xiangrong. Study on Instantaneous Imaging Model of Aerial Time Series Images[J]. 测绘通报, 2017, 0(12): 33-37.

References

[1] 王之卓.摄影测量原理[M].武汉:武汉大学出版社,2007.
[2] 宋爽,杨健,王涌天.全局光流场估计技术及展望[J].计算机辅助设计与图形学学报,2014,26(5):841-850.
[3] 李秀智,贾松敏,尹晓琳,等.视觉光流矢量场估计算法综述[J].北京工业大学学报,2013,39(11):1638-1643.
[4] 涂志刚,谢伟,熊淑芬,等.一种高精度的TV-L1光流算法[J].武汉大学学报(信息科学版),2012,37(4):496-499.
[5] ALVAREZ L,WEICKERT J,SÁNCHEZ J.Reliable Estimation of Dense Optical Flow Fields with Large Displacements[J].International Journal of Computer Vision,2000,39(1):41-56.
[6] SEVILLAGLARA L,SUN Deqing,LEARNED-MILLER E G, et al. Optical Flow Estimation with Channel Constancy[C]//Proceedings of the 13th European Conferenceon Computer Vision.Switzerland:Springer,2014:423-438.
[7] BRUHN A,WEICKERT J,SCHNÖRR C.Lucas/Kanade Meets Horn/Schunck:Combining Local and Global Optic Flow Methods[J].International Journal of Computer Vision,2005,61(3):211-231.
[8] 陈震,张聪炫,晏文敬,等.基于图像局部结构的区域匹配变分光流算法[J].电子学报,2015,43(11):2200-2209.
[9] 李秀智,尹晓琳,贾松敏,等.改进的TVGL1平滑光流估计[J].光学学报,2013,33(10):1015-1017.
[10] 李庆忠,何东晓.基于聚类的背景建模与运动目标检测方法[J].计算机工程与应用,2008,44(8):193-195.
[11] STAUFER C,GRIMSON W E L.Adaptive Background Mixture Models for Real-time Tracking[C]//Proc. of IEEE Conference on Computer Vision and Pattern Recognition.[S.l.]:IEEE,1999:246-252.
[12] TOOYAMA K,KRUMM J,BRUMIT B,et a1.Principles and Practice of Background Maintenance[C]//Proc. ICCV.Corfu,Greece:IEEE,1999:246-261.
[13] 闫利,巩翼龙,张毅,等.光流动态纹理在土地利用/覆盖变化检测研究中的应用[J].光谱学与光谱分析,2014,34(11):3056-3061.
[14] 曹凤海,宋占武,李燕,等. 无人机航摄拍照瞬间精确空间位置的确定[J]. 测绘通报, 2016(6):144-145.
[15] 李志学,颜紫科,张曦. 无人机测绘数据处理关键技术及应用探究[J]. 测绘通报, 2017(S1):38-43.
[16] 邓非, 张祖勋,张剑清. 基于序列影像的城市三维建模[J]. 计算机工程, 2007, 33(8):208-209.
[17] 王霞,张过,沈欣,等. 顾及像面畸变的卫星视频稳像[J]. 测绘学报, 2016, 45(2):194-198.
[18] 张过. 卫星视频处理与应用进展[J]. 应用科学学报, 2016, 34(4):361-370.