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A novel change detection approach for VHR remote sensing images by integrating multi-scale features

机译：通过集成多尺度特征，一种新颖的改变VHR遥感图像的检测方法

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摘要

A novel change detection (CD) method for very high-resolution images is proposed by integrating multi-scale features. First, a novel edge density matching index was designed, and the structural similarity of textures, including grey level co-occurrence matrix, Gaussian Markov random field, and Gabor features between bitemporal images, were extracted to measure changes. Then, an adaptive approach was proposed to select optimal textures based on the majority consistency between spectrum and textures. Afterward, all features were decomposed into multi-scale features and fused into initial CD maps using Dempster-Shafer evidence theory. Finally, advantage fusion was implemented to generate the final CD map by fusing initial CD maps to remove noise and preserve details. Experiments conducted on real SPOT 5 and simulated QuickBird datasets, which achieved the total error ratios of 8.74% and 2.50%, respectively, indicate the effectiveness of the proposed approach.
机译：通过集成多尺度特征，提出了一种用于非常高分辨率图像的新颖改变检测（CD）方法。首先，设计了一种新的边缘密度匹配指数，并提取包括灰度共发生矩阵，高斯马尔可夫随机字段和衡量标记之间的Gabor特征的纹理的结构相似性，以测量变化。然后，提出了一种基于频谱和纹理之间的大多数一致性选择最佳纹理的自适应方法。之后，所有特征都分解成多尺度特征，并使用Dempster-Shafer证据理论融合成初始CD地图。最后，实现了优势融合以通过熔化初始CD图来生成最终CD地图以去除噪声并保留细节。在实位置5和模拟Quickbird数据集上进行的实验，其分别实现了8.74％和2.50％的总误差比，表明了所提出的方法的有效性。

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  • 来源
    《International journal of remote sensing》 |2019年第14期|4910-4933|共24页
  • 作者

    Hao Ming; Shi Wenzhong; Ye Yuanxin; Zhang Hua; Deng Kazhong;

  • 作者单位

    China Univ Min & Technol NASG Key Lab Land Environm & Disaster Monitoring Xuzhou Jiangsu Peoples R China;

    Hong Kong Polytech Univ Dept Land Surveying & Geoinformat Hong Kong Peoples R China;

    Southwest Jiaotong Univ Fac Geosci & Environm Engn Chengdu Sichuan Peoples R China;

    China Univ Min & Technol NASG Key Lab Land Environm & Disaster Monitoring Xuzhou Jiangsu Peoples R China;

    China Univ Min & Technol NASG Key Lab Land Environm & Disaster Monitoring Xuzhou Jiangsu Peoples R 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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