To delete watermarks from pictures using deep learning, we need to implement an encoder-decoder network. The encoder network takes the input image and maps it to a lower-dimensional feature space, while the decoder network maps the lower-dimensional features back to the original image. In between encoder and decoder, we can add a layer to perform the watermark deletion.
Here is the MATLAB code to implement an encoder-decoder network, where the input image is first preprocessed and then passed through the encoder network.
main.m848 chars30 lines
Note that the encoderLayers
and decoderLayers
variables should be defined using appropriate layers (e.g., convolutional or pooling layers) depending on the specific network architecture being used. The watermarkRemovalLayer
variable should also be defined appropriately (e.g., as a convolutional or fully connected layer). Finally, the trained network can be used to remove watermarks on new images by passing them through the encoder-decoder network.
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