An additive and lossless watermarking method based on invariant image approximation and Haar wavelet transform

In this article, we propose a new additive lossless watermarking scheme which identifies parts of the image that can be reversibly watermarked and conducts message embedding in the conventional Haar wavelet transform coefficients. Our approach makes use of an approximation of the image signal that is invariant to the watermark addition for classifying the image in order to avoid over/underflows. The method has been tested on different sets of medical images and some usual natural test images as Lena. Experimental result analysis conducted with respect to several aspects including data hiding capacity and image quality preservation, shows that our method is one of the most competitive existing lossless watermarking schemes in terms of high capacity and low distortion.