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Method and system for extracting and classifying features of hyperspectral remote sensing image

机译:高光谱遥感图像特征提取与分类方法及系统

摘要

The present invention provides a method for extracting and classifying features of hyperspectral remote sensing image, including: an sampling step, a binarizing step, a coding step, a statistical calculating step, a concatenating step, and a classifying step. The present invention further provides a system for extracting and classifying features of hyperspectral remote sensing image. The technical solution provided by the present invention can make full use of the contextual relationship between the spectral domain and the spatial domain in a hyperspectral remote sensing image by extending two-dimensional LBPs into three-dimensional LBPs, and has good robustness to noise by introducing a relaxation threshold discrimination operation. Furthermore, the rotation-invariant three-dimensional LBP model provided by the present invention takes account of the essential characteristics of the hyperspectral remote sensing image, and therefore the present solution has advantages that it is targeted, simple in operation and high in calculation efficiency.
机译:本发明提供一种高光谱遥感图像特征的提取和分类方法,包括:采样步骤,二值化步骤,编码步骤,统计计算步骤,并置步骤和分类步骤。本发明还提供了一种用于提取和分类高光谱遥感图像特征的系统。本发明提供的技术方案通过将二维LBP扩展为三维LBP,可以充分利用高光谱遥感图像中光谱域与空间域之间的上下文关系,并且通过引入将其具有良好的抗噪声能力松弛阈值判别操作。此外,本发明提供的旋转不变三维LBP模型考虑了高光谱遥感图像的本质特征,因此本解决方案具有针对性,操作简单,计算效率高的优点。

著录项

  • 公开/公告号US10509984B2

    专利类型

  • 公开/公告日2019-12-17

    原文格式PDF

  • 申请/专利权人 SHENZHEN UNIVERSITY;

    申请/专利号US201815978189

  • 发明设计人 SEN JIA;JIE HU;LIN DENG;

    申请日2018-05-13

  • 分类号G06K9;G06K9/62;G06K9/46;

  • 国家 US

  • 入库时间 2022-08-21 11:29:18

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