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.
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[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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