基于时空信息的作物光谱图像相关模型挖掘方法

doi:10.16182/j.issn1004731x.joss.201812003

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (12): 4513-4519.doi: 10.16182/j.issn1004731x.joss.201812003

基于时空信息的作物光谱图像相关模型挖掘方法

高荣华^1,2,3,4, 李奇峰^1,2,3,4, 顾静秋^1,2,3,4, 孙想^1,2,3,4

1.北京农业信息技术研究中心,北京 100097;
2.国家农业信息化工程技术研究中心,北京 100097;
3.农业部农业信息技术重点实验室,北京 100097;
4.北京市农业物联网工程技术研究中心,北京 100097

收稿日期:2018-06-28 修回日期:2018-07-03 出版日期:2018-12-10 发布日期:2019-01-03

Mining Method of Crop Spectral and Image Correlation ModelBased on Spatio-Temporal Information

Gao Ronghua^1,2,3,4, Li Qifeng^1,2,3,4, Gu Jingqiu^1,2,3,4, Sun Xiang^1,2,3,4

1. Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China;
3. Key Laboratory for Information Technologies in Agriculture, Ministry of Agriculture, Beijing 100097, China;
4. Beijing Engineering Research Center of Agricultural Internet of Things, Beijing 100097, China

Received:2018-06-28 Revised:2018-07-03 Online:2018-12-10 Published:2019-01-03
About author:Gao Ronghua (1977-), female, Cangzhou, Hebei, China, doctor, associate researcher, research direction is decision making for agricultural multimedia information technology and big data analysis.
Supported by:
National Natural Science Foundation of China (61771058)

摘要/Abstract

摘要： 作物病害表现在叶片形态上,且外观和内部结构发生变化,生长环境也对病害有一定的影响。将生长环境、叶RGB图像和光谱图像融合,研究并提出一种作物光谱图像相关模型的时空信息挖掘方法,从时间维度、空间维度和光谱维度分析作物病害的光谱反射特征与作物发育、健康状况和生长条件的相关性,建立典型病害特征模型。实验结果表明,图像处理和光谱成像技术的融合方法可以在疾病的早期阶段实现快速、准确和无损诊断。

关键词: 高斯滤波, 光谱信息, 时空信息, 时间维, 谱维数

Abstract: When crop disease occurs, it is often displayed in the leaf, and the appearance and internal structure of the crop are changed, and the growth environment also has a certain influence on the disease. The growth environment, leaf RGB images and spectral images are fused to study the sparse feature recognition method of crop diseases based on information combination of multi spectral images. In this paper, a spatial-temporal information mining method for crop spectral and image correlation models is studied. The correlation between spectral reflectance characteristics of crop diseases and crop development, health status and growth conditions are analyzed from time dimension, space dimension and spectral dimension, and disease characteristics is established. The experimental results show that the fusion method of image processing and spectral imaging technology can achieve fast, accurate and nondestructive diagnosis in the early stage of disease.

Key words: Gaussian filtering, spectral information, spatio-temporal information, time dimension, spectral dimension

中图分类号:

TP391

高荣华, 李奇峰, 顾静秋, 孙想. 基于时空信息的作物光谱图像相关模型挖掘方法[J]. 系统仿真学报, 2018, 30(12): 4513-4519.

Gao Ronghua, Li Qifeng, Gu Jingqiu, Sun Xiang. Mining Method of Crop Spectral and Image Correlation ModelBased on Spatio-Temporal Information[J]. Journal of System Simulation, 2018, 30(12): 4513-4519.

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基于时空信息的作物光谱图像相关模型挖掘方法

Mining Method of Crop Spectral and Image Correlation ModelBased on Spatio-Temporal Information

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