Applications of neural network to watermarking capacity
Image watermarking capacity research is to study how much information can be hidden in an image. In watermarking schemes, watermarking can be viewed as a form of communication and the image can be considered as a communication channel to transmit messages. Almost all previous works on watermarking capacity are based on information theory, using Shannon formula to calculate the capacity of watermarking.
This paper presents a blind watermarking algorithm using a Hopfield neural network, and analyzes watermarking capacity based on the neural network. Result shows that the attraction basin of associative memory decideswatermarking capacity.
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