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Analysis of spatial distribution pattern of change-detection error caused by misregistration

机译：配准错误引起的变化检测误差的空间分布格局分析

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摘要

Misregistration between multitemporal remotely sensed images is one of the significant sources of change-detection errors. In this study, spatial distribution of change-detection errors induced by misregistration was analysed quantitatively. First, multitemporal images are registered with different misregistration values measured by root mean square error (RMSE) from 0 to 1 pixels. The image differencing method, one of the most widely used change-detection methods, is then used to detect changes. Finally, the spatial distribution pattern of change-detection errors caused by misregistration is analysed using buffering analysis based on multitemporal image edges. Experimental results indicate that the commission errors caused by misregistration values from 0 to 1 pixels are almost always within 1 pixel of the edge, regardless of image resolution. In addition, the omission errors falling within 1 pixel of the edges are about 70% for medium-resolution images. The omission errors falling within 1 or 2 pixels of the edges for high-resolution images can be as much as 50% to 60%. This work improves the understanding of spatial distribution of change-detection errors caused by misregistration and shows the relations between these errors and image edges. Moreover, it is helpful for developing new methods by combining edge and spatial information to reduce the adverse effects of misregistration on change-detection.
机译：多时相遥感图像之间的配准错误是变化检测错误的重要来源之一。在这项研究中，定量分析了因配准错误而导致的变化检测错误的空间分布。首先，将多时相图像与从0到1像素的均方根误差（RMSE）测量的不同配准值配准。然后，使用图像差异化方法（使用最广泛的变化检测方法之一）来检测变化。最后，利用基于多时相图像边缘的缓冲分析方法，分析了因配准错误而引起的变化检测误差的空间分布规律。实验结果表明，与图像分辨率无关，由0到1像素的重合度值引起的佣金错误几乎总是在边缘的1像素以内。此外，对于中分辨率图像，落在边缘1个像素内的遗漏误差约为70％。对于高分辨率图像，落在边缘的1或2像素之内的遗漏误差可能高达50％到60％。这项工作使人们更好地理解了因配准错误而引起的变化检测错误的空间分布，并显示了这些错误与图像边缘之间的关系。此外，通过结合边缘和空间信息来减少错误配准对变化检测的不利影响，有助于开发新方法。

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  • 来源
    《International journal of remote sensing》 |2013年第20期|6883-6897|共15页
  • 作者

    Wenzhong Shi; Ming Hao;

  • 作者单位

    Joint Research Laboratory on Spatial Information, The Hong Kong Polytechnic University and Wuhan University, Wuhan and Hong Kong, China;

    School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
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