A Novel Cluster-Based Difference Expansion Transform for Lossless Data Hiding

In this paper, we propose a lossless data hiding algorithm for grayscale images. Specifically, our technique is based on the cluster-based difference expansion transform. The main scenario behind our technique is that we use a recursive cluster construction technique to divide the input image into several clusters. In the data embedding process, a modified difference expansion transform is used to embed the secret message into the pixels cluster by cluster. Experimental results show that our technique can achieve high embedding capacity from 0.56 to 0.85 bpp while the PSNR value is over 30 db. The technique provides a reversible method and has been demonstrated to be feasible in image data hiding.