A novel quantum representation of color digital images

In this paper, we propose a novel quantum representation of color digital images (NCQI) in quantum computer. The freshly proposed quantum image representation uses the basis state of a qubit sequence to store the RGB value of each pixel. All pixels are stored into a normalized superposition state and can be operated simultaneously. Comparison results with the latest multi-channel representation for quantum image reveal that NCQI can achieve a quadratic speedup in quantum image preparation. Meanwhile, some NCQI-based image processing operations are discussed. Analyses and comparisons demonstrate that many color operations can be executed conveniently based on NCQI. Therefore, the proposed NCQI model is more flexible and better suited to carry out color quantum image processing.     

SQR: a simple quantum representation of infrared images

A simple quantum representation (SQR) of infrared images is proposed based on the characteristic that infrared images reflect infrared radiation energy of objects. The proposed SQR model is inspired from the Qubit Lattice representation for color images. Instead of the angle parameter of a qubit to store a color as in Qubit Lattice representation, probability of projection measurement is used to store the radiation energy value of each pixel for the first time in this model. Since the relationship between radiation energy values and probability values can be quantified for the limited radiation energy values, it makes the proposed model more clear. In the process of image preparation, only simple quantum gates are used, and the performance comparison with the latest flexible representation of quantum images reveals that SQR can achieve a quadratic speedup in quantum image preparation. Meanwhile, quantum infrared image operations can be performed conveniently based on SQR, including both the global operations and local operations. This paper provides a basic way to express infrared images in quantum computer.     

A flexible representation of quantum images for polynomial preparation, image compression, and processing operations

A Flexible Representation of Quantum Images (FRQI) is proposed to provide a representation for images on quantum computers in the form of a normalized state which captures information about colors and their corresponding positions in the images. A constructive polynomial preparation for the FRQI state from an initial state, an algorithm for quantum image compression (QIC), and processing operations for quantum images are combined to build the whole process for quantum image processing on FRQI. The simulation experiments on FRQI include storing, retrieving of images and a detection of a line in binary images by applying quantum Fourier transform as a processing operation. The compression ratios of QIC between groups of same color positions range from 68.75 to 90.63% on single digit images and 6.67–31.62% on the Lena image. The FRQI provides a foundation not only to express images but also to explore theoretical and practical aspects of image processing on quantum computers.     

Quantum representation and watermark strategy for color images based on the controlled rotation of qubits

In this paper, a novel quantum representation and watermarking scheme based on the controlled rotation of qubits are proposed. Firstly, a flexible representation for quantum color image (FRQCI) is proposed to facilitate the image processing tasks. Some basic image processing operations based on FRQCI representation are introduced. Then, a novel watermarking scheme for quantum images is presented. In our scheme, the carrier image is stored in the phase \(\theta \) of a qubit; at the same time, the watermark image is embedded into the phase \(\phi \) of a qubit, which will not affect the carrier image’s visual effect. Before being embedded into the carrier image, the watermark image is scrambled to be seemingly meaningless using quantum circuits, which further ensures the security of the watermark image. All the operations mentioned above are implemented by the controlled rotation of qubits. The experimental results on the classical computer show that the proposed watermarking scheme has better visual quality under a higher embedding capacity and outperforms the existing schemes in the literature.     

基于混沌序列的量子图像加密方案

针对量子图像加密问题,设计一种基于混沌序列的加密方案。首先,采用NEQR模型描述量子图像,然后,采用3种混沌序列和受控旋转门使每个颜色比特随机旋转±π/4弧度,完成加密过程。解密时,首先根据密钥生成混沌序列,然后使每个颜色比特随机旋转π/4弧度即可。该方法加密后的直方图呈均匀分布,且密钥空间大,抗攻击能力强。经典计算机上的仿真结果表明该方法有较好的安全性。     

Controlling the quantum-memory-assisted entropic uncertainty relation by quantum-jump-based feedback control in dissipative environments

Quantum Information Processing - Based on the NEQR of quantum images, a new quantum gray-scale image watermarking scheme is proposed through Arnold scrambling and least significant bit (LSB)...     

一种基于密钥的受控最低有效位修改技术的稳健型量子水印算法

如何更好地保护量子图像的版权，是量子水印技术的一个重要研究课题。基于对数极坐标的量子图像表示，提出了一种新颖的量子水印算法。根据通信双方共享一组密钥的值，发送方选择量子载体图像像素灰度值的高四位中的某一位作为受控位；再根据所选受控位的值，发送方将水印信息嵌入到量子载体图像的最低有效位或次最低有效位上。这种基于密钥的受控最低有效位修改技术，提高了量子水印图像的透明性和稳健性。基于MATLAB的实验仿真和性能分析，也表明新算法在透明性、稳健性和嵌入容量上有着良好的表现。     

A quantum watermarking scheme using simple and small-scale quantum circuits

A new quantum gray-scale image watermarking scheme by using simple and small-scale quantum circuits is proposed. The NEQR representation for quantum images is used. The image sizes for carrier and watermark are assumed to be \(2n \times 2n\) and \(n \times n\), respectively. At first, a classical watermark with \(n \times n\) image size and 8 bits gray scale is expanded to an image with \(2n \times 2n\) image size and 2 bits gray scale. Then the expanded image is scrambled to be a meaningless image by the SWAP gates that controlled by the keys only known to the operator. The scrambled image is embedded into the carrier image by the CNOT gates (XOR operation). The watermark is extracted from the watermarked image by applying operations in the reverse order. Simulation-based experimental results show that our proposed scheme is excellent in terms of three items, visual quality, robustness performance under noises, and computational complexity.     

一种彩色图像的量子描述方法及应用

为了提高量子彩色图像的存储效率,提出一种新的量子彩色图像描述方法.在该方法中,像素的位置信息采用多比特量子系统的基态描述,像素的三基色灰度值信息只采用一个量子比特描述,具体描述为该量子比特的相位.利用这种描述方法,给出量子彩色图像的几种简单操作方法,包括像素三基色灰度值的改变、互换,图像位置翻转、置换,设计一种新的量子图像水印的实现方法.所提出的方法可在将来的量子计算机上执行.经典计算机上的仿真结果验证了该方法的有效性.     

Least significant qubit algorithm for quantum images

To study the feasibility of the classical image least significant bit (LSB) information hiding algorithm on quantum computer, a least significant qubit (LSQb) information hiding algorithm of quantum image is proposed. In this paper, we focus on a novel quantum representation for color digital images (NCQI). Firstly, by designing the three qubits comparator and unitary operators, the reasonability and feasibility of LSQb based on NCQI are presented. Then, the concrete LSQb information hiding algorithm is proposed, which can realize the aim of embedding the secret qubits into the least significant qubits of RGB channels of quantum cover image. Quantum circuit of the LSQb information hiding algorithm is also illustrated. Furthermore, the secrets extracting algorithm and circuit are illustrated through utilizing control-swap gates. The two merits of our algorithm are: (1) it is absolutely blind and (2) when extracting secret binary qubits, it does not need any quantum measurement operation or any other help from classical computer. Finally, simulation and comparative analysis show the performance of our algorithm.     

基于独立成分分析和IHS变换域的灰度可见光和红外图像融合

针对灰度可见光和红外图像的融合图像缺乏色彩信息、图像的高阶信息在变换域中统计独立性不足的缺陷, 提出一种基于独立分量分析和IHS (亮度-色度-饱和度) 变换域的融合方法. 该方法利用IHS 变换域能够有效分离图像亮度分量和彩色信息的优势, 对灰度可见光图像建立灰度图像的彩色传递模型. 利用各分量的独立性进行基于独立分量分析和IHS 变换域的图像融合, 并得到最终的彩色融合图像, 使融合图像更加符合人类视觉要求. 仿真实验验证了所提出算法的有效性.

     

Multi-image encryption scheme based on quantum 3D Arnold transform and scaled Zhongtang chaotic system

A quantum representation model for multiple images is firstly proposed, which could save more storage space than the existing quantum image representation models and allow quantum hardware to encrypt an arbitrary number of images simultaneously. Moreover, the definition and the quantum circuit of quantum 3D Arnold transform are given based on the proposed quantum representation model for multiple images. Furthermore, a novel quantum multi-image encryption scheme is devised by combining quantum 3D Arnold transform and quantum XOR operations with scaled Zhongtang chaotic system. Theoretically, the proposed quantum image encryption scheme could encrypt many images simultaneously. Numerical simulations and theoretical analyses demonstrate that the proposed quantum multi-image encryption scheme outperforms both its classical counterparts and the existing typical quantum image encryption algorithms in terms of security, robustness, encryption capacity and computational complexity.     

NEQR量子图像下的差分扩展可逆数据隐藏算法

量子图像安全处理是一个新兴的研究领域,而量子图像数据隐藏是量子图像安全处理技术的一种,在不损害载体的情况下可用于保护量子图像的版权和认证量子图像是否完整。目前尚缺乏对量子图像可逆数据隐藏的详细技术研究。结合差值扩展技术,本文提出了一种量子图像可逆数据隐藏算法：1）选用NEQR量子图像表示法来表示图像;2）借鉴经典的差值扩展算法,在NEQR量子图像上对量子比特进行处理,可逆嵌入数据;3）设计了信息嵌入、信息提取和载体无损恢复的量子线路图,并进行了仿真。基于经典图像的实验结果表明,本文算法是可逆的,可用于将来对量子图像的认证和保护。     

G-quadtree: A hierarchical representation of gray-scale digital images

We proposeG-quadtree as a hierarchical representation method for gray-scale digital images. G-quadtree is an extended quadtree each leaf of which holds a multi level-value. An algorithm constructing a G-quadtree from the array representation of a gray-scale image is described, implemented and tested. The algorithm is established in such a way that the conventional binary array-to-quadtree conversion algorithm is applied to each bit of array elements repeatedly in descending order of significance. Space efficiency analysis reveals that G-quadtree representation is sufficient in a particular application to a color coding of macroautoradiography of rat brains.     

基于视觉感知机理的大容量彩色图像盲隐写算法

针对现有彩色图像隐写算法大多将灰度图像的算法直接用于彩色通道,未能运用彩色视觉感知机理的问题,提出一种YUV空间上的、基于视觉感知机理的大容量彩色图像盲隐写算法。主要方法是在Y分量上通过标准差来分析载体图像的局部复杂性,利用视觉感知机理将信息分成两部分隐写于Y和V分量中,灵活性较差的U分量则作为隐写信息的通道指示器,无需大的改变。大量实验结果表明,所提算法与其他方法相比在嵌入大容量信息后依然能够保持很好的不可感知性,而且可以抵抗直方图对比和RS隐写分析方法,因而所提算法是合理、简洁、有效的。     

基于指纹特征数据的水印技术研究

传统水印技术的水印数据主要有两种:伪随机序列(一维)和二值图像(二维).本文通过分别对图像的R,G,B信道嵌入水印信息,提出了一种将256级灰度的指纹图像嵌入到宿主图像的算法,宿主图像可以是256级灰度图像,也可以是24位的真彩图像.通过实验表明该算法具有良好的鲁棒性.     

一种基于含水印量子图像的自适应量子隐写算法

利用NEQR量子图像表示法,提出了一种能在含水印量子载体图像中实现隐蔽通信的量子隐写算法。新算法借助水印通常拥有很好的稳健性和其特有的自恢复系统,对秘密信息的稳健性进行了多重强化。相比于之前的量子隐写算法,新算法不仅强化了秘密信息自身的稳健性,而且通过量子线路的设计提高了其嵌入和提取的可执行性和执行效率。经实验仿真结果和性能分析验证,新算法在保留原有隐蔽性和安全性基础上,进一步提高了秘密信息的稳健性和嵌入率。     

一种利用回归神经网络黑白图像着色算法研究

研究了利用神经网络对序列黑白(灰度)图像进行着色的问题。针对以往基于人工或者半自动化技术的黑白图像着色技术效率低下、视觉效果较差的缺陷,提出了一种利用三层神经网络、无须人工干预的图像自动着色算法。首先将灰度图像分割成小块,通过对小块提取灰度特征、空间特征等作为神经网络的输入,训练得到一个回归神经网络。在着色过程中,可以利用该神经网络将图像中各像素由灰度空间投影到一个经过压缩的色彩空间,从而实现了图像的自动着色过程。实验结果显示本方法能有效地将灰度图像着色,并且由于使用了一个压缩的色彩空间,使得计算效率和着色效果都得到了有效的提高,能很好地逼近原始的真实图像。     

基于点扩散和误差扩散的半色调自隐藏算法

将秘密图像隐藏在一幅基于点扩散或误差扩散的半色调图像中,实现基于点扩散和误差扩散的半色调自隐藏算法;以基于点扩散的双向共轭信息隐藏算法为基础实现基于点扩散的灰度半色调自隐藏算法,将该算法扩展到基于误差扩散的灰度半色调图像,提出基于误差扩散的灰度半色调自隐藏算法;以最新的基于点扩散和误差扩散的新共轭数据隐藏算法为基础,提出基于点扩散和误差扩散的彩色半色调自隐藏算法。将四类自隐藏算法进行实验验证,对不同半色调自隐藏算法的性能进行了比较。结果表明在相同参数下,基于误差扩散的彩色半色调自隐藏算法具有最好的性能。     

单参数控制的灰度图像着色

灰度图像着色是计算机图形学和计算机图像处理等领域的研究热点,在影视制作、数字照片编辑、动漫艺术等方面具有重要的应用价值。传统的方法通过大量的交互操作实现灰度图像中不同区域的聚类或者色源图像和灰度图像之间的匹配,大大降低了着色的效率。提出一种新的基于单参数控制的灰度图像着色方法。首先,利用球体几何理论建立色彩变换模型。其次,基于线性回归的方法,对色源图像和灰度图像的直方图分别进行多项式拟合建模。用户输入拟合多项式的阶数之后,可以实现色源图像和灰度图像的自动聚类并建立它们之间的匹配关系。最后,通过色源图像和灰度图像之间的颜色映射实现灰度图像的着色。该方法无须烦琐的用户交互,使得着色过程更为方便快捷。