Applications of neural network to watermarking capacity
Fan Zhang, Hongbin Zhang · 2005
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 decides watermarking capacity.