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In 2015, Lu proposed the (k, F1) interpolation-based reversible hiding scheme by using the center folding strategy (CFS) to improve the image quality of the interpolation neighboring pixels scheme. In Lu's scheme, k is used to define the total number of thresholds for categories of the complexity of the block, and F1 is the length of the secret message that can be concealed in the smoothest area. The hiding performance of Lu's scheme for the smooth image is great. However, the results of that scheme for complex images can still be improved. Therefore, this paper proposed an enhanced interpolation-based hiding scheme by modifying the structure of the CFS from having a single layer to having multiple layers. The secret data are encoded by the multiple-layer folding table to reduce the distortion between the original image and the stego-image. Experimental results show that the image quality and the payload of the proposed scheme are better than those of the other schemes. [ABSTRACT FROM AUTHOR]

Inspired by reversible data hiding methods that applied the PE (predicted error) strategy will have the advantage of good performances. It means that the closer the PE approaches its climax, the higher embedding capacity and image quality will have. This paper provides four stages of two-phase reversible data hiding method to produce prediction images with Lagrange interpolation on odd and even pixels, and to hide confidential information into the differences between the predicted image and the original image. Lagrange interpolation will be crossly applied on odd and even pixels to produce predicted images, and then histogram shifting modification will be applied to embed secret data into. The experimental results demonstrate the quality of Lena image from this scheme has a PSNR value of 43.97 dB and an embedding capacity of 0.38 bpp, for one level. For enhancing the embedding capacity to 0.98 bpp, our scheme can still maintain a PSNR value of 31.14 dB. From the demonstrated results, it can be obvious to know that our proposed algorithm has superior performances in terms of image quality and embedding capacity than that the algorithms of Ni et al. and Tai et al. [ABSTRACT FROM AUTHOR]

In this paper, we present a robust and imperceptible image steganography (IS) scheme for covert communication. A substantial literature presented on IS is distortion based that radically affects image imperceptibility. These schemes conceal secret information in LSBs or MSBs of cover image by using simple or random substitution. The usage of LSBs and MSBs makes these schemes vulnerable to malicious attacks like Chi-square attack and sample pair attack, and specifically, the MSBs affect the imperceptibility of cover image. Additionally, these schemes endure low capacity as large numbers of cover image pixels are required for hiding even low volume of information. The proposed IS scheme is distortion free as the negligible PVD of cover and secret image is utilized for information hiding. In contrast to LSB- or MSB-based information hiding schemes, we proposed FEM method that compares the entropy of frequencies of secret and cover image for information hiding. In fact, the elevated rate of FEM leads to high imperceptibility and capacity. Moreover, the proposed scheme uses multilayer approach that has layered transformations to frequency domain for improved robustness. Experimental investigation demonstrates that the proposed scheme has better PSNR and BPP with enhanced robustness and imperceptibility in contrast to existing schemes. [ABSTRACT FROM AUTHOR]

Transform-based techniques partially address challenges like robustness and the imperceptibility in image steganography. Such approaches, however, increase the memory requirement and reduce the quality of the cover image and hiding capacity. Moreover, the steganography is always coupled with cryptography to strengthen the confidentiality. This paper presents an adaptive hybrid method for image steganography procedure based on bit reduction and pixel adjustment using the fuzzy logic and integer wavelet transform technique. The fuzzy set theory provides powerful tools to represent and process human knowledge in the form of fuzzy if-then rules that can resolve difficulties in image processing arising due to the uncertainty of the data, tasks, and results. We apply a bit reduction algorithm to each byte of the data which are to hide in the cover image. This decreases the memory usage and increases the capacity. The embedding of the input text into the cover image distorts the cover image. Hence, to minimize the visual difference between the cover image and the text embedded image, an optimum pixel adjustment algorithm is applied to the text embedded image. Simulation results demonstrate the effectiveness of our proposed approach. [ABSTRACT FROM AUTHOR]