gistlib - autoencoder to remove watermarks in matlab

To remove watermarks from an image using an autoencoder in MATLAB, follow the steps below:

Load the watermarked image.


img = imread('watermark.png');
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Convert the image to grayscale and resize it to a manageable size.


img = imresize(rgb2gray(img), [256 256]);
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Create a copy of the original image to use as the input for the autoencoder.


noisy_img = img;
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Generate the watermark to be removed using a similar size and shape as the image.


watermark = imread('watermark.png');
watermark = imresize(rgb2gray(watermark), [256 256]);
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Add the watermark to the image to create the watermarked image.


watermarked_img = img + watermark;
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Normalize the noisy image and watermarked image.


noisy_img = double(noisy_img)/255;
watermarked_img = double(watermarked_img)/255;
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Define the architecture of the autoencoder, the number of layers, and the size of the bottleneck layer.


input_size = size(noisy_img);
latent_dimension = 64;
encoder = [
    imageInputLayer(input_size, 'Normalization', 'none', 'Name', 'input')  
    fullyConnectedLayer(512, 'Name', 'encoder_fc1')
    reluLayer('Name', 'encoder_relu1')
    fullyConnectedLayer(256, 'Name', 'encoder_fc2')
    reluLayer('Name', 'encoder_relu2')
    fullyConnectedLayer(128, 'Name', 'encoder_fc3')
    reluLayer('Name', 'encoder_relu3')
    fullyConnectedLayer(latent_dimension, 'Name', 'encoder_fc4')
    reluLayer('Name', 'encoder_relu4')
    ];
decoder = [
    fullyConnectedLayer(128, 'Name', 'decoder_fc1')
    reluLayer('Name', 'decoder_relu1')
    fullyConnectedLayer(256, 'Name', 'decoder_fc2')
    reluLayer('Name', 'decoder_relu2')
    fullyConnectedLayer(512, 'Name', 'decoder_fc3')
    reluLayer('Name', 'decoder_relu3')
    fullyConnectedLayer(prod(input_size), 'Name', 'decoder_fc4')
    reshapeLayer(input_size, 'Name', 'output')
    ];
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Combine the encoder and decoder networks to create the autoencoder.


layers = [encoder; decoder];
lgraph = layerGraph(layers);
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Define the options and train the autoencoder using the noisy image as the input and the watermarked image as the target output.


options = trainingOptions('adam', ...
    'MaxEpochs', 200, ...
    'MiniBatchSize', 64, ...
    'Verbose', true);

[net, train_info] = trainNetwork(noisy_img, watermarked_img, lgraph, options);
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Use the trained autoencoder to remove the watermark from the image.


pred = predict(net, noisy_img);
denoised_img = uint8(pred*255);

figure; 
subplot(1,3,1); imshow(img); title('Original Image');
subplot(1,3,2); imshow(watermarked_img); title('Watermarked Image');
subplot(1,3,3); imshow(denoised_img); title('Denoised Image');
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Note: The quality of the watermarked image and the watermark itself can have a significant impact on the performance of the autoencoder. In some cases, the watermark may not be completely removed or may leave artifacts in the denoised image.

autoencoder to remove watermarks in matlab

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