测绘通报 ›› 2022, Vol. 0 ›› Issue (2): 116-120.doi: 10.13474/j.cnki.11-2246.2022.0054

• 技术交流 • 上一篇    下一篇

基于色调饱和度亮度模型的可见光植被提取

程滔1, 管林杰2, 郑新燕1, 陶舒1, 高崟1   

  1. 1. 国家基础地理信息中心, 北京 100830;
    2. 长江空间信息技术工程有限公司(武汉), 湖北 武汉 430010
  • 收稿日期:2021-03-07 修回日期:2021-05-16 发布日期:2022-03-11
  • 作者简介:程滔(1981-),男,硕士,高级工程师,主要从事自然资源调查监测技术研究、地表覆盖信息提取与变化监测方法研究、摄影测量与遥感影像数据处理与应用开发等工作。E-mail:chengtao@ngcc.cn
  • 基金资助:
    国家地理国情监测专项(21-30-01-5)

Visible light vegetation extraction of hue saturation and lightness color model

CHENG Tao1, GUAN Linjie2, ZHENG Xinyan1, TAO Shu1, GAO Yin1   

  1. 1. National Geomatics Center of China, Beijing 100830, China;
    2. Changjiang Space Information Technology Engineering Co., Ltd., Wuhan 430010, China
  • Received:2021-03-07 Revised:2021-05-16 Published:2022-03-11

摘要: 针对遥感影像只具有红(R)、绿(G)、蓝(B)3个可见光波段时无法利用归一化植被指数(NDVI)方法提取植被信息的现状,本文提出了一种基于色调饱和度亮度(HSL)模型的可见光植被提取方法。利用自主研发的系统,将影像从RGB彩色空间变换至HSL彩色空间,构建归一化色调亮度植被指数(NHLVI),通过分析植被与非植被信息在HSL彩色空间中的特征,以及NHLVI、H、S、L、R、G、B各分量的特征,确定协同NHLVI、S分量提取植被信息,利用B分量特征剔除结果中的非植被信息,从而实现植被信息提取,并提高提取精度。研究表明,该方法在现有NHLVI指数方法基础上,加入S分量,提升了可见光植被提取的精度及方法的适用性。

关键词: 植被提取, 归一化色调亮度植被指数, 色调, 饱和度, 亮度

Abstract: As remote sensing images that only have three visible light bands: red (R), green (G) and blue (B) cannot use normalized difference vegetation index (NDVI) method to extract vegetation land cover information, a new method based on hue saturation and lightness color model is proposed. The image is transformed from RGB color space to HSL color space by using the self-developed system, and normalized hue lightness vegetation index (NHLVI) is constructed. By analyzing the characteristics of vegetation and non-vegetation information in HSL color space, and the characteristics of NHLVI, H, S, L, R, G, B, the vegetation information is extracted by cooperating with NHLVI and S indexes, and the non-vegetation information in the result is eliminated by using B component feature, so as to realize vegetation information extraction and improve the extraction accuracy. The results show that this method could improve the accuracy of visible light vegetation extraction and the applicability of the method by adding S index to the existing NHLVI index method.

Key words: vegetation extraction, NHLVI, hue, saturation, lightness

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