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

doi:10.16182/j.issn1004731x.joss.201812003

Journal of System Simulation ›› 2018, Vol. 30 ›› Issue (12): 4513-4519.doi: 10.16182/j.issn1004731x.joss.201812003

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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)

Abstract

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

CLC Number:

TP391

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

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