Reversible watermarking based on invariant image classification and dynamical error histogram shifting.

In this article, we present a novel reversible watermarking scheme. Its originality stands in identifying parts of the image that can be watermarked additively with the most adapted lossless modulation between: Pixel Histogram Shifting (PHS) or Dynamical Error Histogram Shifting (DEHS). This classification process makes use of a reference image derived from the image itself, a prediction of it, which has the property to be invariant to the watermark addition. In that way, watermark embedded and reader remain synchronized through this image of reference. DEHS is also an original contribution of this work. It shifts predict-errors between the image and its reference image taking care of the local specificities of the image, thus dynamically. Conducted experiments, on different medical image test sets issued from different modalities and some natural images, show that our method can insert more data with lower distortion than the most recent and efficient methods of the literature.

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.

Comparison of some reversible watermarking methods in application to medical images.

Several reversible watermarking schemes have been proposed for images of sensitive content, like medical imaging, for which any modification may affect their interpretation. In this work, we distinguish these methods according to the way watermark insertion is conducted: additive and substitutive. Some of these approaches have been tested on different sets of medical images issued from three distinct modalities: Magnetic Resonance Images, Positron Emission Tomography and Ultrasound Imaging. Comparison analysis has been conducted with respect to several aspects including data hiding capacity and image quality preservation. Experimental results show different limitations which depend on the watermark approach but also on image modality specificities.