A Hyper-Chaotically Encrypted Robust Digital Image Watermarking Method with Large Capacity Using Compress Sensing on a Hybrid Domain.

The digital watermarking technique is a quite promising technique for both image copyright protection and secure transmission. However, many existing techniques are not as one might have expected for robustness and capacity simultaneously. In this paper, we propose a robust semi-blind image watermarking scheme with a high capacity. Firstly, we perform a discrete wavelet transformation (DWT) transformation on the carrier image. Then, the watermark images are compressed via a compressive sampling technique for saving storage space. Thirdly, a Combination of One and Two-Dimensional Chaotic Map based on the Tent and Logistic map (TL-COTDCM) is used to scramble the compressed watermark image with high security and dramatically reduce the false positive problem (FPP). Finally, a singular value decomposition (SVD) component is used to embed into the decomposed carrier image to finish the embedding process. With this scheme, eight 256×256 grayscale watermark images are perfectly embedded into a 512×512 carrier image, the capacity of which is eight times over that of the existing watermark techniques on average. The scheme has been tested through several common attacks on high strength, and the experiment results show the superiority of our method via the two most used evaluation indicators, normalized correlation coefficient (NCC) values and the peak signal-to-noise ratio (PSNR). Our method outperforms the state-of-the-art in the aspects of robustness, security, and capacity of digital watermarking, which exhibits great potential in multimedia application in the immediate future.

Routing strategy on a two-dimensional small-world network model.

Based on a two-dimensional small-world network model, we propose an efficient routing strategy that enhances the network capacity while keeping the average packet travel time low. We deterministically increase the weight of the links attached to the "congestible nodes" and compute the effective distance of a path by summing up the weight of the links belong to that path. The routing cost of a node is a linear combination of the minimum effective distance from the node to the target and its queue length. The weight assignment reduces the maximum load of the network, while the incorporation of dynamic information further balances the traffic on the network. Simulation results show that the network capacity is much improved compared with the reference strategies, while the average packet travel time is relatively small.