A sea ice sample augmentation method, system, and apparatus

Abstract

The application provides a sea ice sample augmentation method, system and device, relates to the cross field of sea ice sample processing and computer vision, and the method comprises the steps of: labeling and preprocessing a ship-based sea ice image to obtain a standardized real sea ice scene graph and a corresponding sea ice label graph; constructing an improved conditional generative adversarial network comprising a generator and a double-head discriminator, wherein the double-head discriminator comprises a spatial domain discriminator and a wavelet domain discriminator; inputting the sea ice label graph into the generator to generate a sea ice scene graph; combining the generated graph and the label graph into a first input group, combining the real graph and the label graph into a second input group, inputting the two input groups into the two discriminators respectively to obtain spatial domain and wavelet domain discrimination results; generating a composite loss function according to the discrimination results, updating the parameters through back propagation; repeating the process until the loss converges to obtain a trained model; and inputting a sea ice label graph to be augmented into the model to output a sea ice augmented sample by the generator. The application can generate high-quality sea ice samples with global structure and detailed texture, and can alleviate the shortage of samples.

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