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Image-based efficient PM2.5 concentration prediction method

A concentration prediction and image technology, applied in image analysis, image enhancement, image data processing, etc., can solve the problem of unable to afford the cost of setting up monitoring points and maintaining instruments, high cost, etc.

Active Publication Date: 2022-07-05
BEIJING UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the above-mentioned sensor-based PM2.5 measurement method inevitably brings high costs, and most regions cannot afford the cost of setting up monitoring points and maintaining instruments

Method used

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  • Image-based efficient PM2.5 concentration prediction method
  • Image-based efficient PM2.5 concentration prediction method
  • Image-based efficient PM2.5 concentration prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0023] The first step is to extract the saturation S(x, y) of the RGB format image, the method is as follows:

[0024]

[0025] where x and y are the pixels at the horizontal and vertical positions of the image, respectively; U(x, y)=max[R(x, y), G(x, y), B(x, y)], U(x, y) y) is the largest value in the R, G, and B components of the picture; V(x, y)=min[R(x, y), G(x, y), B(x, y)], V(x, y) is the smallest value in the R, G, B components of the picture.

[0026] The second step is to calculate the entropy H of the image saturation in the spatial domain s ,Methods as below:

[0027]

[0028] where D H is the height of the image saturation space and D M is the width of the image saturation space, and P(i, j) is the probability density.

[0029] The third step is to decompose the saturation space into 10 bands through the Haar wavelet transform technology, and calculate the entropy of the wavelet coefficients of each band Methods as below:

[0030]

[0031] The sat...

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Abstract

The invention discloses an image-based high-efficiency PM2.5 concentration prediction method. The scene images are acquired by mobile phones or cameras, and the PM2.5 concentration is estimated in real time based on these images. First, a large number of pictures were taken in a good weather environment with very low PM2.5 concentration, and a natural statistical model (NS) was established based on the entropy features of the space and transform domains. Then a new image is compared with the NS model to calculate the degree of deviation. Finally, a nonlinear function was used to map the deviation of the PM2.5 concentration index. A large number of experimental results show that the model proposed by the present invention has great advantages compared with the current advanced methods in terms of accurate prediction of PM2.5 concentration and realization efficiency.

Description

technical field [0001] The invention belongs to a PM2.5 concentration prediction method, uses pictures and a natural scene statistical model suitable for PM2.5 to predict the PM2.5 concentration, and can effectively realize real-time and accurate PM2.5 concentration prediction. Background technique [0002] In recent decades, rapid urbanization and industrialization are causing the deterioration of air quality, which has become a global problem. Among all air pollutions, PM2.5 has attracted more and more people's attention due to the destruction of the respiratory system, cerebrovascular and cardiovascular functions of the human body. The current methods and instruments for measuring PM2.5 concentration mainly measure PM2.5 weight through physical and chemical methods. The PM2.5 is collected on the filter paper, and then a beam of beta ray is irradiated. When the ray passes through the filter paper and particulate matter, it is attenuated due to scattering. The degree of at...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/20064G06T2207/20076G06T2207/30168
Inventor 顾锞乔俊飞李晓理
Owner BEIJING UNIV OF TECH