An Image Encryption Scheme Based on Logistic Quantum Chaos

This paper proposes an image encryption scheme based on logistic quantum chaos. Firstly, we use compressive sensing algorithms to compress plaintext images and quantum logistic and Hadamard matrix to generate the measurement matrix. Secondly, the improved flexible representation of the quantum images (FRQI) encoding method is utilized for encoding the compressed image. The pixel value scrambling operation of the encoded image is realized by rotating the qubit around the axis. Finally, the quantum pixel is encoded into the pixel value in the classical computer, and the bit-level diffusion and scrambling are performed on it. Numerical analysis and simulation results show that our proposed scheme has the large keyspace and strong key sensitivity. The proposed scheme can also resist standard attack methods such as differential attacks and statistical analysis.     

Wavelet-modified binary phase-only morphological correlation for color pattern recognition

This paper reports a morphological phase-only correlation technique based on bit-map representation for recognition of color as well as grey images in a hybrid digital-optical correlation architecture. The color image is decomposed into its R, G and B components, and each component is further decomposed into eight disjoint elementary images depending upon the bit-map representation of the color value at each pixel. Bit-map representation of the pixel values of an image reduces the required computational time. A set of twenty-four disjoint wavelet-modified binary phase-only filters (WBPOFs) are generated from these bit-map decomposed images. The target image is similarly decomposed into eight disjoint images each of R, G and B and their digital Fourier transforms multiplied with the corresponding WBPOFs. The product functions thus obtained are added up to form a single resultant product function, whose optical Fourier transformation gives the correlation peaks for the presence of R, G and B components in the image. The single product function overcomes the necessity of obtaining the final optical Fourier transformation of the R, G and B components separately. The novelty of this approach lies in the fact that the WBPOFs synthesized by this procedure are thus able to identify both colored as well as gray images and can tolerate salt-and-pepper noise to a considerable extent.     

Improved Quantum Image Median Filtering in the Spatial Domain

In some image processing algorithms, such as those for image feature extraction and segmentation, filtering is a significant pre-processing step to remove noises and improve image quality. An improved quantum image median filtering approach is proposed, and its corresponding quantum circuit is designed in this work. The main idea of the approach is that first the classical image is converted into a quantum version based on the novel enhanced quantum representation (NEQR) of digital images, and then a unique quantum module is designed to realize the median calculation of neighborhood pixels for each pixel point in the image. Finally, in order to improve the filtering effect, extremum detection is employed to distinguish noises from true signals. The experimental results show that a competitive filtering performance is obtained compared with previous methods. In addition, a network complexity analysis of the quantum circuit suggests that the proposed filtering approach can perform enormous speed-up over its corresponding classical counterparts.

     

Fuzzy Matching Based on Gray-scale Difference for Quantum Images

Quantum image processing has recently emerged as an essential problem in practical tasks, e.g. real-time image matching. Previous studies have shown that the superposition and entanglement of quantum can greatly improve the efficiency of complex image processing. In this paper, a fuzzy quantum image matching scheme based on gray-scale difference is proposed to find out the target region in a reference image, which is very similar to the template image. Firstly, we employ the proposed enhanced quantum representation (NEQR) to store digital images. Then some certain quantum operations are used to evaluate the gray-scale difference between two quantum images by thresholding. If all of the obtained gray-scale differences are not greater than the threshold value, it indicates a successful fuzzy matching of quantum images. Theoretical analysis and experiments show that the proposed scheme performs fuzzy matching at a low cost and also enables exponentially significant speedup via quantum parallel computation.     

Quantum Point Cloud and its Compression

Quantum computation is becoming an important and effective tool to overcome the high real-time computational requirements of classical digital image processing. The quantum representations of two-dimensional images have been a lot of achievements. However, there are only few methods to express a three-dimensional image by quantum representation. In this paper, a three-dimensional quantum representation for digital images — quantum point cloud is proposed. Moreover, a lossy compression method is used to reduce the complexity of preparation.     

QRDA: Quantum Representation of Digital Audio

Multimedia refers to content that uses a combination of different content forms. It includes two main medias: image and audio. However, by contrast with the rapid development of quantum image processing, quantum audio almost never been studied. In order to change this status, a quantum representation of digital audio (QRDA) is proposed in this paper to present quantum audio. QRDA uses two entangled qubit sequences to store the audio amplitude and time information. The two qubit sequences are both in basis state: |0〉 and |1〉. The QRDA audio preparation from initial state |0〉 is given to store an audio in quantum computers. Then some exemplary quantum audio processing operations are performed to indicate QRDA’s usability.     

A Novel LSB Based Quantum Watermarking

Quantum watermarking is a technique which embeds the invisible quantum signal such as the owners identification into quantum multimedia data (such as audio, video and image) for copyright protection. In this paper, using a quantum representation of digital images a new quantum watermarking protocol including quantum image scrambling based on Least Significant Bit (LSB) is proposed. In this protocol, by using m-bit embedding key K₁ and m-bit extracting key K₂ a m-pixel gray scale image is watermarked in a m-pixel carrier image by the original owner of the carrier image. For validation of the presented scheme the peak-signal-to-noise ratio (PSNR) and histogram graphs of the images are analyzed.     

A Novel Quantum Image Compression Method Based on JPEG

Quantum image processing has been a hot topic. The first step of it is to store an image into qubits, which is called quantum image preparation. Different quantum image representations may have different preparation methods. In this paper, we use GQIR (the generalized quantum image representation) to represent an image, and try to decrease the operations used in preparation, which is also known as quantum image compression. Our compression scheme is based on JPEG (named from its inventor: the Joint Photographic Experts Group) — the most widely used method for still image compression in classical computers. We input the quantized JPEG coefficients into qubits and then convert them into pixel values. Theoretical analysis and experimental results show that the compression ratio of our scheme is obviously higher than that of the previous compression method.     

单色CCD记录多波长数字全息图及再现像彩色显示

对多波长数字全息图的记录和再现像的彩色显示问题进行了研究.从菲涅耳近似算法出发,对在记录距离一定情况下,不同波长全息图数字再现像的像元所表示的几何尺寸会因波长不同而不同,从而导致各波长再现像无法重合的情况进行了讨论.通过理论分析,讨论了不同波长全息图像素数与再现像像元之间的关系、不同波长全息图记录距离与再现像像元之间的关系,据此得出的解决不同波长再现像重合问题的方法及其对再现像的影响和适用范围等问题；并对合成再现像中原始色彩信息改变及其解决办法进行了分析.通过无透镜傅里叶变换数字全息方法,以632.8 nm和532.0 nm两种波长的激光为光源,用单色CCD进行记录,验证了方法的可行性.     

Controlling image size as a function of distance and wavelength in Fresnel-transform reconstruction of digital holograms

A method for controlling the size of amplitude and phase images reconstructed from digital holograms by the Fresnel-transform method is proposed and demonstrated. The method can provide a constant reconstruction pixel width in the reconstructed image plane, independent of the recording and reconstruction distance. The proposed method makes it possible to maintain the size of an object for a sequence of digital holograms recorded at different distances and, therefore, to subtract phase maps for an object recorded at different distances. Furthermore, the method solves the problem of superimposition in multiwavelength digital holography for color display and holographic interferometry applications.     

Gray images embedded in a color image and encrypted with FRFT and Region Shift Encoding methods

In this paper, we have proposed a new multiple image encryption and watermarking technique. Several gray images can be watermarked in the three channels of an enlarged color image. The neighbor pixel value addition and subtraction algorithm is used to realize blind watermarking, therefore the original host color image does not need in extraction the watermark image. The gray images are encrypted with FRFT and Region Shift Encoding techniques before hiding to enhance the security. The robustness against occlusion attacks and noise attacks are also analyzed. And some computer simulations are presented to verify the possibility.     

Multimodality Image Fusion Based on Quantum Wavelet Transform and Sum-Modified-Laplacian Rule

The parallelism and entanglement characteristics of quantum computation greatly improve the efficiency of image processing tasks. With the sharp increase of data size and requirement of real-time processing in image fusion application, rapid implementation using quantum computation will become the inexorable trend. A novel multimodality image fusion algorithm based on quantum wavelet transform (QWT) and proposed quantum version of sum-modified-laplacian (SML) rule is designed in this paper. The source digital images are firstly represented by flexible representation of quantum image (FRQI) model, and then the quantum form images are transformed with QWT to capture salient features of source images. The quantum version of SML rule is proposed to fuse wavelet coefficients, which has higher efficiency and runs faster than its classical counterpart. The final fused image is obtained by using inverse quantum wavelet transform. The simulations and theoretical analysis verify that the proposed algorithm is effective in the fusion of multimodality images.

     

Quantum Image Edge Extraction Based on Improved Sobel Operator

Edge extraction is a basic task in image processing. This paper proposes a quantum image edge extraction algorithm based on improved sobel operator for the generalized quantum image representation (GQIR) to solve the real-time problem. The quantum image model of GQIR can store arbitrary quantum images with a size of H × W. Our scheme can calculate the gradients of image intensity of all the pixels simultaneously. Then, the concrete circuits of quantum image edge extraction algorithm are implemented by using a series of quantum operators which have been designed. Compared with existing quantum edge extraction algorithms, our scheme can achieve more accurate edge extraction, especially for diagonal edges. Finally, the complexity of the quantum circuits were been analyzed based on the basic quantum gates and give the simulation experiment results on classical computer.

     

Equivalence of a Bit Pixel Image to a Quantum Pixel Image

We propose a new method to transform a pixel image to the corresponding quantum-pixel using a qubit per pixel to represent each pixels classical weight in a quantum image matrix weight. All qubits are linear superposition, changing the coefficients level by level to the entire longitude of the gray scale with respect to the base states of the qubit. Classically, these states are just bytes represented in a binary matrix, having code combinations of 1 or 0 at all pixel locations. This method introduces a qubit-pixel image representation of images captured by classical optoelectronic methods.     

Equivalence of a Bit Pixel Image to a Quantum Pixel Image

We propose a new method to transform a pixel image to the corresponding quantum-pixel using a qubit per pixel to represent each pixels classical weight in a quantum image matrix weight.All qubits are linear superposition,changing the coefficients level by level to the entire longitude of the gray scale with respect to the base states of the qubit.Classically,these states are just bytes represented in a binary matrix,having code combinations of 1 or 0 at all pixel locations.This method introduces a qubit-pixel image representation of images captured by classical optoelectronic methods.     

Derivation of the analytical solution of Color2Gray algorithm and its application to fast color removal based on color quantization

In order to convert a color image into a monochrome one, the lightness components of pixels have to date been used as gray-levels for the representation of the monochrome image. However, saliencies of an image embedded only in the chrominance components are eliminated in such conversion. To cope with this problem, “Color2Gray” algorithm, which excels in the color removal of digital images, has been proposed by Gooch et al. [ACM Trans. Graphics 24 (2005) 634]. In this paper, the algorithm is first analyzed and its mathematical property is revealed. Then a fast Color2Gray algorithm is proposed by using the mathematical property. Finally, the validity and the effectiveness of the proposed algorithm are proven by some experiments.     

A Secret Sharing Scheme for Quantum Gray and Color Images Based on Encryption

This paper is concerned with the better security of quantum image secret sharing (QISS) algorithm. The improved QISS (IQISS) scheme is implemented on both quantum gray image (FRQI) and quantum color image (MCQI). The new IQISS scheme comprises efficient sharing process and recovering process. The core idea of the sharing process is to combine encryption and measurement for two types of quantum secret images to acquire the quantum shadow images. In the recovering process, strip operation is firstly utilized on the shadow images. Afterwards, the decryption algorithm is used to recover the original quantum secret image. Experiments demonstrate that significant improvements in the security are in favor of the proposed approach.

     

Encryption and decryption of images with chaotic map lattices

We propose a secure algorithm for direct encryption and decryption of digital images with chaotic map lattices. The basic idea is to convert, pixel by pixel, the image color to chaotic logistic maps one-way coupled by initial conditions. After small numbers of iterations and cycles, the image becomes indistinguishable due to inherent properties of chaotic systems. Since the maps are coupled, the image can be completely recovered by the decryption algorithm if map parameters, number of iterations, number of cycles, and the image size are exactly known.     

离散分数阶随机变换与加权直方图交叉置乱的双图像加密算法

为了实现对两幅图像进行同步加密,降低传输负载并提高密文的抗明文攻击能力,提出了离散分数阶随机变换与加权像素混沌置乱的双图像加密算法。将2个分阶参数引入到Tent映射中,设计了新的Tent映射;根据明文像素值,构建加权像素直方图模型,联合位外部密钥,生成改进的Tent映射的初值;再利用初值对分数阶Tent映射进行迭代,输出2组随机序列,对2幅明文进行位置交叉混淆,获取2个置乱密文;基于DWT(discrete wavelet transform)技术,对2个置乱密文进行稀疏表示;根据混沌序列,定义随机循环矩阵,联合稀疏表示,获取2个置乱密文对应的测量矩阵。根据随机掩码与调制相位掩码,建立数据融合模型,将2个测量矩阵组合为复合矩阵;基于离散分数阶随机变换,对复合图像进行扩散,获取密文。测试数据显示:与已有的多图像加密方案相比,该算法的抗明文攻击能力与用户响应值更理想,密文的NPCR、UACI值分别达到了99.83%、34.57%。该算法具有较高的加密安全性,能够有效抵御网络中的外来攻击,确保图像安全传输。