Destroy the Robust Commercial Watermark via Deep Convolutional Encoder-Decoder Network

Abstract

Nowadays, robust watermark is widely used to protect the copyright of multimedia. Robustness is the most important ability for watermark in application. Since the watermark attacking algorithm is a good way to promote the development of robust watermark, we proposed a new method focused on destroying the commercial watermark. At first, decorrelation and desynchronization are used as the preprocessing method. Considering that the train set of thousands of watermarked images is hard to get, we further use the Bernoulli sampling and dropout in network to achieve the training instance extension. The experiments show that the proposed network can effectively remove the commercial watermark. Meanwhile, the processed image can result in good quality that is almost as good as the original image.