In this paper, a novel image watermarking method is proposed which is based on discrete wave transformation (DWT), Hessenberg decomposition (HD), and singular value decomposition (SVD). First, in the embedding process, the host image is decomposed into a number of sub-bands through multilevel DWT, and the resulting coefficients of which are then used as the input for HD. The watermark is operated on the SVD at the same time. The watermark is finally embedded into the host image by the scaling factor. Fruit fly optimization algorithm, one of the natural-inspired optimization algorithms is devoted to find the scaling factor through the proposed objective evaluation function. The proposed method is compared to other research works under various spoof attacks, such as the filter, noise, JPEG compression, JPEG2000 compression, and sharpening attacks. The experimental results show that the proposed image watermarking method has a good trade-off between robustness and invisibility even for the watermarks with multiple sizes.INDEX TERMS Image watermarking, discrete wave transformation, singular value decomposition, Hessenberg decomposition, fruit fly optimization algorithm.

This paper proposes a parallel digital image encryption algorithm based on a piecewise linear chaotic map (PWLCM) and a four-dimensional hyper-chaotic map (FDHCM). Firstly, two decimals are obtained based on the plain-image and external keys, using a novel parallel quantification method. They are used as the initial value and control parameter for the PWLCM. Then, an encryption matrix and four chaotic sequences are constructed using the PWLCM and FDHCM, which control the permutation and diffusion processes. The proposed algorithm is implemented and tested in parallel based on a Graphics Processing Unit (GPU) device. Numerical analysis and experimental results show that the proposed algorithm achieves a high encryption speed and a good security performance, which provides a potential solution for real-time image encryption applications.

In terms of Chua's circuit system, compressive sensing (CS) and Haar wavelet, a novel image compression-encryption scheme (CES) is proposed in this paper. Firstly, the plaintext image is decomposed into approximate component and detail components through Haar wavelet. Then the approximate component is diffused by the threshold processing of local binary patterns (LBP) operator-based chaotic sequence which is produced by the combination of Chua's circuit and Logistic map. Next, the Lissajous map is applied to generate the chaos-combined asymptotic deterministic random measurement matrices (CADRMM) which are employed to measure the detail components in different compression ratios. In addition, the combination of mapped approximate and detail components is shuffled by the Logistic map. The experimental results and simulation analysis prove that the proposed cryptosystem is capable of reducing data for transmission and has good security performance under various attacks, especially for the shear and noise attacks.

In this paper, we propose an efficient and self-adapting colour-image encryption algorithm based on chaos and the interactions among multiple red, green and blue (RGB) layers. Our study uses two chaotic systems and the interactions among the multiple layers to strengthen the cryptosystem for the colour-image encryption, which can achieve better confusion and diffusion performances. In the confusion process, we use the novel Rubik's Cube Scheme (RCS) to scramble the image. The significant advantage of this approach is that it sufficiently destroys the correlation among the different layers of colour image, which is the most important feature of the randomness for the encryption. The theoretical analysis and experimental results show that the proposed algorithm can improve the encoding efficiency, enhances the security of the cipher-text, has a large key space and high key sensitivity, and is also able to resist statistical and exhaustive attacks.

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