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首页> 外文期刊>International journal of remote sensing >Detecting changes in high-resolution satellite coastal imagery using an image object detection approach
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Detecting changes in high-resolution satellite coastal imagery using an image object detection approach

机译：使用图像对象检测方法检测高分辨率卫星沿海图像的变化

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摘要

This article presents a spatial contrast-enhanced image object-based change detection approach (SICA) to identify changed areas using shape differences between bi-temporal high-resolution satellite images. Each image was segmented and intrinsic image objects were extracted from their hierarchic candidates by the proposed image object detection approach (IODA). Then, the dominant image object (DIO) presentation was labelled from the results of optimal segmentation. Comparing the form and the distribution of bi-temporal DIOs by using the raster overlay function, ground objects were recognized as being spatially changed where the corresponding image objects were detected as merged or split into geometric shapes. The result of typical spectrum-based change detection between two images was enhanced by using changed spatial information of image objects. The result showed that the change detection accuracies of the pixels with both attribute and shape changes were improved from 84% to 94% for the strong attribute pixel, and from 36% to 81% for the weak attribute pixel in study area. The proposed approach worked well on high-resolution satellite coastal images.
机译：本文提出了一种基于空间对比度增强的图像基于对象的变化检测方法（SICA），该方法可以使用双时相高分辨率卫星图像之间的形状差异来识别变化区域。通过提出的图像对象检测方法（IODA）对每个图像进行分割，并从其候选层次中提取出内部图像对象。然后，从最佳分割结果中标记主要图像对象（DIO）表示。通过使用栅格叠加功能比较双时DIO的形式和分布，可以将地面对象识别为空间变化，而将相应的图像对象检测为合并或拆分为几何形状。通过使用图像对象的变化空间信息，可以增强两个图像之间基于光谱的典型变化检测结果。结果表明，在研究区域中，属性和形状都发生变化的像素的变化检测精度从强属性像素的84％提高到94％，弱属性像素的变化检测精度从36％提高到81％。拟议的方法在高分辨率卫星沿海图像上效果很好。

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  • 来源
    《International journal of remote sensing》 |2013年第8期|2454-2469|共16页
  • 作者

    Jianyu Chen; Zhihua Mao; Bill Philpot; Jonathan Li; Delu Pan;

  • 作者单位

    State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography,State Oceanic Administration, Hangzhou 310012, PR China;

    State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography,State Oceanic Administration, Hangzhou 310012, PR China;

    School of Civil and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA;

    Department of Geography and Environmental Management, University of Waterloo, Waterloo, ON, Canada N2L 3G1;

    State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography,State Oceanic Administration, Hangzhou 310012, PR 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
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