Reversible Watermarking for Low Distortion Using Transform

Reversible watermarking enables the embedding of useful information in a host signal without any loss of host information. Tian’s difference-expansion technique is a high-capacity, reversible method for data embedding. However, the method suffers from undesirable distortion at low embedding capacities and lack of capacity control due to the need for embedding a location map. The propose a low distortion transform for predictionerror expansion reversible watermarking. The transform is derived by taking a simple linear predictor and by embedding the expanded prediction error not only into the current pixel but also into its prediction context. The proposed transform introduces less distortion than the classical prediction-error expansion for complex predictors such as the median edge detector or the gradient-adjusted predictor. Reversible watermarking algorithms based on the proposed transform are analyzed.The Bit-rate and PSNR values are compared. A reversible watermarking algorithm with very high data hiding capacity has been developed for color images. The algorithm allows the watermarking process to be reversed, which restores the exact original image. In addition, to maximize the amount of data that can be hidden into an image, the embedding algorithm can be applied recursively an across the color components.