Contourlet-Based Image Watermarking Using Optimum Detector in a Noisy Environment

Abstract

In this paper, an improved multiplicative image watermarking system is presented. Since human visual system is less sensitive to the image edges, watermarking is applied in the contourlet domain, which represents image edges sparsely. In the presented scheme, watermark data is embedded in directional subband with the highest energy. By modeling the contourlet coefficients with General Gaussian Distribution (GGD), the distribution of watermarked noisy coefficients is analytically calculated. The tradeoff between the transparency and robustness of the watermark data is solved in a novel fashion. At the receiver, based on the Maximum Likelihood (ML) decision rule, an optimal detector by the aid of channel side information is proposed. In the next step, a blind extension of the suggested algorithm is presented using the patchwork idea. Experimental results confirm the superiority of the proposed method against common attacks, such as Additive White Gaussian Noise (AWGN), JPEG compression, and rotation attacks, in comparison with the recently proposed techniques.

An efficient robust watermarking scheme for varying sized blocks

“…As is evident from the tables, our scheme produces much better results than the compared technique presented in [9]. Figure 22 shows that for an AWGN attack of variance 30, two versions of our proposed technique (using block size 8 and block size 16) produce lower BER (%) than that of Akhaee et al [9] with four types of host images. Table 11.…”

“…In Tables 11 and 12 the three versions of the proposed scheme are compared with the watermarking scheme presented by Akhaee et al [9] for AWGN noise attack (variance 25 and 30), JPEG compression attack (quality factor 10%), and scaling attack of different levels. As is evident from the tables, our scheme produces much better results than the compared technique presented in [9].…”

“…Akhaee et al [9] Table 12. BER (%) comparison of recovered watermark of length 128 bits between Akhaee et al [9] with block size 16 and proposed scheme with block sizes 8, 16, and 32 under scaling attack of different levels.…”

A Novel Algorithm for Watermarking and Image Encryption

“…when a small perturbation is added to an image, the values do not change significantly. Thus it was oyed for image watermarking [8], [9].…”

“…One of the unique properties of contourlet transform is that we could have any number of directional decompositions at every level of resolutions [3]. Thus making it a one of the suitable technique for watermarking [8] [9], [10].…”