Predicting visible/infrared band images using radar reflectance/backscatter images of a terrestrial region

A method of creating a mapping model for translating an input image to an output image, the method comprising obtaining an ensemble of training data T comprising a sample of pairs of matched images [R,V], providing a neural network and training the neural network with the training data T to obtain the mapping model V*=f(R) that translates input image R to output image V*, where V* is equivalent to the ground truth V in a flawless mapping the method further comprising the following steps:

• a) propagating R into the generator, wherein the generator produces V* which represents a “fake” version of V based on a transformation of R
• b) associating V* with R to form new matched pair [R,V*]
• c) propagating [R,V*] into the discriminator to determine the probability that V* is “real”, wherein the probability that V* is “real” is estimated from a loss function that encodes the quantitative distance between V and V*
• d) backpropagating the error defined by the loss function through the neural network wherein R comprises at least one image in a first frequency range, encoded as a data matrix and wherein V comprises at least one image in a second frequency range, encoded as a data matrix.