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An automatic method for precise 3D registration of high resolution satellite images and Airborne LiDAR Data

机译:高分辨率卫星图像和机载LiDAR数据精确3D配准的自动方法

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摘要

Precise 3D registration of Light Detection and Ranging (LiDAR) data and High-Resolution Satellite Image (HRSI) is the prerequisite in the many remote sensing applications. An automatic registration process involves two main steps including the detection of corresponding entities and the estimation of a relating mathematical model. Typical matching techniques, which are generally developed to match consistent data sources, are prone to fail in case of matching between heterogeneous data sources (e.g. LiDAR and optical images). This paper proposes a three-step method to give in hand an accurate and automatic 3D registration technique between LiDAR data and the HRSI. The first step introduces a new product called Optical Consistent LiDAR Product (OCLP) which is meant to be consistent with HRSI from the radiometric point of view. The OCLP is generated using raster maps of the LiDAR heights and intensities along with information of the sun position at the acquisition time of HRSI. This new product proved to be very promising as a matching entity with HRSI. In the second step, a 3D model is estimated robustly through the matched points identified by the well-known Scale Invariant Feature Transform (SIFT) technique between the OCLP and the HRSI. The last step of the proposed method aims to strengthen this 3D model which is accomplished via iterative closest edge points matching technique. To do so, the coarse 3D model is iteratively improved based on the matching results obtained on the image edges. The proposed method was implemented on 20 different datasets containing various urban textures. The results indicate the effectiveness of the proposed method since in some cases it could achieve to sub-pixel accuracies which are the utmost expectation for a registration technique.
机译:光检测和测距(LiDAR)数据和高分辨率卫星图像(HRSI)的精确3D配准是许多遥感应用中的先决条件。自动注册过程涉及两个主要步骤,包括检测相应实体和估计相关数学模型。通常开发用于匹配一致数据源的典型匹配技术在异构数据源(例如LiDAR和光学图像)之间匹配的情况下容易失败。本文提出了一种分三步的方法,以便在LiDAR数据和HRSI之间提供准确而自动的3D配准技术。第一步是引入一种新产品,称为光学一致性激光雷达产品(OCLP),从辐射角度看,该产品与HRSI保持一致。 OCLP使用LiDAR高度和强度的栅格图以及HRSI采集时间的太阳位置信息生成。事实证明,该新产品作为与HRSI的匹配实体非常有前途。第二步,通过OCLP和HRSI之间的众所周知的尺度不变特征变换(SIFT)技术识别的匹配点,对3D模型进行稳健估计。该方法的最后一步旨在加强此3D模型,这是通过迭代最近边缘点匹配技术完成的。为此,基于在图像边缘获得的匹配结果,迭代地改进了粗略的3D模型。该方法在包含各种城市纹理的20个不同数据集上实现。结果表明了该方法的有效性,因为在某些情况下它可以达到亚像素精度,这是对配准技术的最大期望。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第24期|9460-9483|共24页
  • 作者

  • 作者单位

    Tafresh Univ Dept Geodesy & Surveying Engn Tafresh 3951879611 Iran;

    KN Toosi Univ Technol Fac Geodesy & Geomat Engn Tehran Iran;

  • 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
  • 关键词

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