PM2.5 Concentration Prediction Method Based on Image Quality
A concentration prediction and image quality technology, which is applied in image analysis, image enhancement, image data processing, etc., can solve the problems of low accuracy of PM2.5 concentration estimation, and does not consider the influence of relative humidity on atmospheric imaging, so as to achieve shortened modeling Time, reduce memory space, improve the effect of prediction accuracy
Active Publication Date: 2020-06-19
NANJING UNIV OF SCI & TECH
View PDF3 Cites 0 Cited by
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
[0005] Therefore, the existing PM2.5 prediction methods based on image processing do not consider the influence of relative humidity on atmospheric imaging, resulting in low accuracy of PM2.5 concentration estimation
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 moreImage
Smart Image Click on the blue labels to locate them in the text.
Smart ImageViewing Examples
Examples
Experimental program
Comparison scheme
Effect test
Embodiment Construction
[0027] combine figure 1 , the new method for estimating PM2.5 concentration based on image processing of the present invention comprises the following steps:
[0028] Step 1. Collect natural images regularly at fixed points, and preprocess the images; specifically:
[0029] Step 1-1, filter out images taken on rainy days in the data set;
[0030] Step 1-2, perform image registration on the remaining data sets, select an image as a reference image to register the rest of the images, use the Generalized Dual Bootstrap-ICP algorithm for registration, and select Similarity for the transformation model;
[0031] Steps 1-3. Select a block of the image in the data set as the final training set, remove useless image information, and the image block contains scenes that satisfy the dark channel principle.
[0032] Step 2. Using the dark channel prior theory dehazing algorithm to extract the transmittance map of the collected images; specifically:
[0033] Step 2-1: Perform minimum v...
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
Login to View More Abstract
The invention discloses a PM2.5 concentration prediction method based on image quality and belongs to the image processing technology field. The method comprises the following steps of firstly, carrying out image registering on a collected data set (filtering images shot in a rainy day) and taking an image block satisfying a dark channel principle as a final training set; then, recovering a transmissivity image of the training set, using a sliding window method to extract a characteristic from the transmissivity iamge, carrying out image characteristic standardization and eliminating an influence of a relative humidity; and then, using a robustness regression analysis method to analyze a relation between the extracted characteristic of the training set and a real PM2.5 concentration, and then acquiring a PM2.5 concentration prediction model; and finally completing PM2.5 concentration prediction. An experiment result shows that an algorithm used for predicting the PM2.5 concentration in the invention is better than an existing algorithm; an influence of a relative humidity meteorology condition on atmosphere imaging can be overcome; and the method has an important meaning for PM2.5 concentration monitoring in a daily life.
Description
technical field [0001] The invention relates to a method for predicting PM2.5 concentration, in particular to a method for predicting PM2.5 concentration based on image quality. Background technique [0002] PM2.5 is the general term for all particulate matter suspended in the air with a diameter less than or equal to 2.5 μm. It is an important indicator of air quality and has a great impact on human health. At present, the detection of PM2.5 concentration in the air is done by some large equipment, which are expensive and require regular maintenance. After observation, it is found that there are obvious differences in the quality of images captured under different air quality conditions. Therefore, I want to design a method for building a correlation model between image quality and PM2.5 concentration. The existing PM2.5 concentration prediction methods based on image processing mainly extract some features that can reflect the image quality. In recent years, the followi...
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
Login to View More Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
CPCG06T7/0002G06T2207/10024G06T2207/20021G06T2207/20024G06T2207/20081
Inventor 陈强杨本芊徐琳
Owner NANJING UNIV OF SCI & TECH