Satellite video super-resolution reconstruction method and system based on recurrent neural network
A technology of cyclic neural network and super-resolution reconstruction, which is applied in the field of remote sensing satellite video processing, can solve the problems of satellite video image moving target deformation, not considering the shape and texture of ground objects, and poor super-resolution reconstruction effect, etc.
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[0056] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.
[0057] see figure 1 , a method for super-resolution reconstruction of satellite video images based on a recurrent neural network provided by an embodiment of the present invention, the specific steps are as follows:
[0058] Step 1: Obtain satellite video images and extract them frame by frame to form an image sequence {I 1 ,I 2 ,...,I t ,...,I n}:
[0059] The optical satellite video image acquired in the embodiment has a spatial resolution of 0.92m, covering houses, rivers, green spaces, farmland, and moving vehicles, ships, airplanes and other static features and moving objects. Extract satellite video images frame by frame to obtain image sequences of the same area {I 1 ,I 2 ,...,I t ,...,I n}. Among them, n is the number of images, and t is the serial number of the images.
[0060] Step 2: Carry out multi-scale...
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