Method and device for extracting hyperspectral remote sensing altered mineral information
A technology of hyperspectral remote sensing and altered minerals, which is applied in the field of hyperspectral remote sensing altered mineral information extraction, can solve the problem of high spectral resolution data redundancy, and achieve the effect of ensuring accuracy and accurate correlation
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Embodiment 1
[0070] refer to figure 1 , the methods of hyperspectral remote sensing alteration mineral information extraction include:
[0071] S000: Obtain hyperspectral image data.
[0072] Specifically, combining figure 2 , step S000 includes the following sub-steps:
[0073] S001: Obtain hyperspectral remote sensing data.
[0074] Based on the electromagnetic wave sensor carried by the UAV, the aerial photography of the environment forms hyperspectral remote sensing data, and then transmits it to the ground control base station, and then transmits or copies it to the device memory through the ground control base station, or directly communicates with the UAV controller system through the processor get.
[0075] S002: data preprocessing.
[0076] Among them, data preprocessing refers to the preprocessing of hyperspectral remote sensing data including radiometric calibration and atmospheric correction, and obtains the ground reflectance (or specific emissivity) hyperspectral image ...
Embodiment 2
[0114] refer to Figure 5 , the difference between this embodiment and embodiment 1 is that the low-rank matrix L is obtained t and sparse matrix S t The constraints are different.
[0115] S700: Obtain the information proportion of the noise component.
[0116] Including: preset error tolerance coefficient ε, in the low-rank matrix L t and sparse matrix S t After the loop iteration, the information proportion of the noise component in the decomposition of the two-dimensional matrix X is obtained, namely ,in Represents the square of the Frobenius norm of the two-dimensional matrix X, since X=L+S+N, so Represents the square of the Frobenius norm of the noise matrix N after matrix factorization.
[0117] S800: Determine the information proportion of the noise component and the size of the error tolerance coefficient.
[0118] include: when Stop the loop iteration at this time, which means that L+S can reconstruct the information of X losslessly, otherwise, it means ...
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