Expansion Embedding Techniques for Reversible Watermarking

Abstract

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. We propose a histogram shifting technique as an alternative to embedding the location map. The proposed technique improves the distortion performance at low embedding capacities and mitigates the capacity control problem. We also propose a reversible data-embedding technique called prediction-error expansion. This new technique better exploits the correlation inherent in the neighborhood of a pixel than the difference-expansion scheme. Prediction-error expansion and histogram shifting combine to form an effective method for data embedding. The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion. There is also a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.

An improved reversible image watermarking algorithm based on difference expansion

“…Double detection identification bit method belongs to the first type of gray overflow solution, which is first raised by Thodi and Rodriguez. 22 Generally, the pixels of most carrier images can conduct multiple non-overflow expansion transformation. There are few pixels of double transformation overflow and one-time transformation overflow (as shown in sample 1, sample 2, and sample 3 in Figure 2).…”

Reversible image watermarking in the integer wavelet domain

“…Alattar (2004) improved Tian's pixel-pair difference expansion by using difference expansion of a triple or a quad of pixels and obtained more space to hide secret message. Thodi and Rodriguez (2007) exploited redundancy of neighbouring pixels and proposed the prediction-error based expansion embedding technique. Focus on improving overflow location map, Hu et al (2009) Li et al (2011) proposed an adaptive embedding technology which can embed much more data into smooth region of an image.…”

Novel Prediction Error Based Reversible Data Hiding Method Using Histogram Shifting

“…Thus, Thodi et al expanded prediction errors instead of difference between two neighboring pixels to create space for hiding data, where the prediction method is median edge detector (MED). So that it exploits more close correlations and increase hiding capacity [4]. Moreover, Sachnev et al sorted prediction errors to increase capacity of data hiding [5].…”