QMap - Sample point mean comparison method
The Sample point mean comparison method is one of the general image information extraction methods we have created. It is also a characteristic method to extract information within the effective parameter range by calculating the model parameters from the color of the sample points in the image.
Now according to the software function interface, the introduction is as follows:
1. Sample point collection Zoom in or roam the image, right-click the mouse button, and select the feature sample point. The linear analysis algorithm requires at least 6 points, which can be arbitrarily selected in the list to perform a quick test and test the results. The position of the sample points on the image and the size of the cross can be changed depending on the situation.
After testing and screening, this group of sample points is a representative of characteristic information, which can be saved for later verification or processing of other images.
a) With background + information simplification: On the original image, the extracted information is replaced with a color for quick verification. b) No background + single information: The extracted information is replaced with one color, and the other information is replaced with the background color to obtain a binary image, which is convenient for data filing and other applications. c) No background + information extraction: The extracted information pixels are displayed in the primary color, and the non-information pixels are displayed as the background color, and the effect is very clear. Converting the above three methods can improve the analysis efficiency.
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