Wheat powdery mildew remote sensing monitoring method with disease feature preprocessing function

A technology for wheat powdery mildew and remote sensing monitoring, applied in the field of remote sensing image processing, can solve the problems of poor monitoring accuracy and high redundancy of wheat disease features, and achieve the effects of improving monitoring accuracy and robustness

Active Publication Date: 2018-09-28
ANHUI UNIVERSITY
View PDF5 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the defects of high redundancy of wheat disease characteristics and poor monitoring accuracy in the pr

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wheat powdery mildew remote sensing monitoring method with disease feature preprocessing function
  • Wheat powdery mildew remote sensing monitoring method with disease feature preprocessing function
  • Wheat powdery mildew remote sensing monitoring method with disease feature preprocessing function

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0071] In order to have a further understanding and understanding of the structural features of the present invention and the achieved effects, the preferred embodiments and accompanying drawings are used for a detailed description, as follows:

[0072] like figure 1 As shown, a remote sensing monitoring method for wheat powdery mildew with disease feature preprocessing function described in the present invention uses the relief method to operate efficiently, and by calculating the weight of image features, higher weights are given to features with strong classification ability . Considering that the relief algorithm does not consider the correlation between image features and cannot remove the redundancy between image features, the mRMR method is used to remove the redundancy between image features, and the minimum redundancy between features is obtained. And the subset of features that have the greatest correlation between the feature and the target. Through relief combine...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention relates to a wheat powdery mildew remote sensing monitoring method with a disease feature preprocessing function. Compared with the prior art, the method overcomes the defects of high feature redundancy and poor monitoring precision of wheat diseases. The method comprises the following steps of obtaining and processing remote sensing data; extracting feature variables; processing thefeature variables; building and optimizing a powdery mildew monitoring model; and obtaining a wheat powdery mildew remote sensing monitoring result. By combining relief and mRMR feature selection technologies with a support vector machine optimized through a genetic method, powdery mildew of regional scale is subjected to effective remote sensing monitoring.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing monitoring method for wheat powdery mildew with a disease characteristic preprocessing function. Background technique [0002] Wheat powdery mildew is one of the main diseases in the production process of wheat. It can occur throughout the growth period of wheat, causing serious reduction in yield and quality. After the damage, the yield reduction is generally between 5% and 10%, and it can reach 20% in severe cases. above. Timely and effective monitoring of the occurrence of wheat powdery mildew is of great significance to improve the yield and quality of wheat. [0003] Although the traditional ground survey method has good survey results, it needs a lot of manpower and material resources and is not suitable for large-scale research. Many scholars use meteorological data to monitor and predict crop diseases and insect pests. Wang Heju...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/24143G06F18/29
Inventor 黄林生阮超黄文江张东彦赵晋陵翁士状曾玮丁文娟丁串龙
Owner ANHUI UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products