Polarimetric SAR image change detection method based on depth confidence network
A deep belief network and change detection technology, applied in the field of image processing, can solve the problems that it is difficult to obtain high classification accuracy for polarimetric SAR images, and does not consider the deep feature representation of polarimetric SAR images, so as to improve the accuracy of change detection
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[0063] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0064] see figure 1 , the implementation steps of the polarization SAR image change detection method based on the deep belief network of the present invention are as follows:
[0065] Step 1, input two polarimetric SAR images of the same area with different phases to be detected;
[0066] Step 2, use ENVI software to register the polarization SAR data of the two time phases;
[0067] Step 3, use the refined Lee filter to reduce speckle on the registered image respectively;
[0068] Step 4: Preliminary manual marking of two polarimetric SAR images of the same area in different phases after registration and speckle reduction;
[0069] Step 5, obtain the polarization coherence matrices TA and TB from the polarization scattering matrix S of the two polarization SAR images respectively. In the case of backscattering, because the reciprocity has S HV = S VH = ...
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