Remote sensing image mixed image element decomposition method based on self-organizing mapping neural network
A technology of mixed pixel decomposition and self-organizing mapping, which is applied in the field of remote sensing image processing, can solve the problems of large amount of calculation, easy to fall into local extreme points, etc., and achieve the effect of ensuring robustness and speed
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[0080] 1. Simulate remote sensing image data
[0081] 1) AVIRIS hyperspectral artificial remote sensing data
[0082] First, three mineral endmembers were selected from the AVIRIS hyperspectral mineral endmember spectral library. Figure 6 shows the spectral curves of these three mineral endmembers. Afterwards, three standard abundance value matrices (32×32) satisfying the non-negative constraint of abundance value and the constraint of abundance value sum to 1 are randomly generated, and the endmembers are mixed according to the randomly generated standard abundance value matrix to obtain Blend images as artificial remote sensing images. In the experiment, the artificial remote sensing image was decomposed into mixed pixels, and the decomposed abundance value matrix was compared with the randomly generated standard abundance value matrix to quantitatively evaluate the decomposition accuracy. Root Mean Square Error (Root Mean Square Error, RMSE) and Correlation Coefficient (C...
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