A General Framework of Reversible Data Hiding with Controlled Contrast Enhancement

This paper proposes a two-step general framework for reversible data hiding(RDH)schemes with controllable contrast enhancement.The first step aims at preserving visual perception as much as possible on the basis of achieving high embedding capacity(EC),while the second step is used for increasing image contrast.In the second step,some peak-pairs are utilized so that the histogram of pixel values is modified to perform histogram equalization(HE),which would lead to the image contrast enhancement.However,for HE,the utilization of some peak-pairs easily leads to over-enhanced image contrast when a large number of bits are embedded.Therefore,in our proposed framework,contrast over-enhancement is avoided by controlling the degree of contrast enhancement.Since the second step can only provide a small amount of data due to controlled contrast enhancement,the first one helps to achieve a large amount of data without degrading visual quality.Any RDH method which can achieve high EC while preserve good visual quality,can be selected for the first step.In fact,Gao et al.’s method is a special case of our proposed framework.In addition,two simple and commonly-used RDH methods are also introduced to further demonstrate the generalization of our framework.

Improving the Covertness in the Physical-Layer Authentication

A well-designed Physical-Layer Authentication(PLA)scheme should consider three properties:covertness,robustness,and security.However,the three properties always cause some dilemmas,e.g.,higher covertness leading to lower robustness.This paper concerns the problem of improving the covertness without sacrificing the robustness.This problem is important because of the following reasons:reducing the errors in recovered source message,improving the security,and ease of constructing a multi-factor authentication system.In this paper,we propose three covert PLA schemes to address the problem.In the first scheme,we improve the covertness by reducing the modification ratio on the source message based on an encoding mechanism.In the second scheme,we improve the covertness by optimizing the superimposing angle,which maximizes the minimum distance between the tagged symbols and the boundary line of the demodulation decision for the source message.In the third scheme,referred to as the hybrid scheme,we further improve the covertness by jointly using the advantages of both the above two schemes.Our experimental results show that when the SNR at a legitimate receiver is 25 dB,as compared with the prior scheme,the first scheme improves the covertness by 17:74%,the second scheme improves the covertness by 28:79%,and the third scheme improves the covertness by 32:09%,while they have similar robustness as Received:Aug.07,2020 Revised:Sep.08,2020 Editor:Nanrun Zhou that of the prior scheme.

A New Encryption-Then-Compression Scheme on Gray Images Using the Markov Random Field

Compressing encrypted images remains a challenge.As illustrated in our previous work on compression of encrypted binary images,it is preferable to exploit statistical characteristics at the receiver.Through this line,we characterize statistical correlations between adjacent bitplanes of a gray image with the Markov random field(MRF),represent it with a factor graph,and integrate the constructed MRF factor graph in that for binary image reconstruction,which gives rise to a joint factor graph for gray images reconstruction(JFGIR).By exploiting the JFGIR at the receiver to facilitate the reconstruction of the original bitplanes and deriving theoretically the sum-product algorithm(SPA)adapted to the JFGIR,a novel MRF-based encryption-then-compression(ETC)scheme is thus proposed.After preferable universal parameters of the MRF between adjacent bitplanes are sought via a numerical manner,extensive experimental simulations are then carried out to show that the proposed scheme successfully compresses the first 3 and 4 most significant bitplanes(MSBs)for most test gray images and the others with a large portion of smooth area,respectively.Thus,the proposed scheme achieves significant improvement against the state-of-the-art leveraging the 2-D Markov source model at the receiver and is comparable or somewhat inferior to that using the resolution-progressive strategy in recovery.

Accelerating the HS-type Richardson Iteration Method with Anderson Mixing

The Accelerated Hermitian/skew-Hermitian type Richardson(AHSR)iteration methods are presented for solving non-Hermitian positive definite linear systems with three schemes,by using Anderson mixing.The upper bounds of spectral radii of iteration matrices are studied,and then the convergence theories of the AHSR iteration methods are established.Furthermore,the optimal iteration parameters are provided,which can be computed exactly.In addition,the application to the model convection-diffusion equation is depicted and numerical experiments are conducted to exhibit the effectiveness and confirm the theoretical analysis of the AHSR iteration methods.