Improved multiple watermarking algorithm for Medical Images

Abstract

At present, most watermarking algorithms use linear correlation method to detect watermarks. However, when the original media signal does not obey the Gaussian distribution, or the watermark is not embedded into the media object to be protected, this method has certain problems. The imperceptibility constraint of digital watermark determines that watermark detection is a weak signal detection problem. Using this feature, firstly, based on the statistical characteristics of DCT (discrete cosine transform) and DWT (discrete wavelet transform), the generalized Gaussian distribution is used to establish its statistical distribution model. Then, the watermark detection problem is transformed into a binary hypothesis test problem. The basic theory of weak signal detection in non-Gaussian noise is used as the theoretical detection model of multiplication watermarking, and the optimized multiply embedded watermark detection algorithm is derived. The algorithm is tested. The results show that the proposed watermark detector has good detection performance for the blind detection of watermarking with unknown embedding strength. Therefore, the detector can be applied in the copyright protection of digital media data.