Nonlinear analysis algorithms are one of the important methods for general image information extraction we created. Compared with the linear analysis algorithm, the accuracy is higher, and the effect is obvious in the accurate classification.
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 7 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.
2. Save and load sample points
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.
3. How to display results
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.
4. The use of channel combination in the algorithm
The nonlinear algorithm includes different combinations of Red, Green and Blue channels as parameters, and there are three ways: RGB Channel combination, GRB Channel combination, and BGR Channel combination, which can be adapted to different applications.
5. Information color and background color of the result graph are optional
6. Quick test
After selecting the sample point, click the test button to automatically complete the modeling operation, display the parameters, and quickly test the results of the range seen on the screen. After selecting sample points, modifying model parameters, and repeating the test many times, satisfactory results can be achieved. After the test, press the Process button to process the full image.
7. There are two sets of parameters in the model parameters that can be changed, and corresponding graph curves can be viewed, changed parameters, and checked the results, which are fast and effective, so they can be adapted to various feature information.
8. After the test, verification and processing of a characteristic information, the entire model parameters are uniquely determined. The save plan provides saving the complete parameters as a special plan file, which can be used in batch processing and repeated combination in the future.
Comments
Post a Comment