Image scrambling on classical computers has been widely studied, however, the corresponding quantum algorithms are rare. This paper proposes a block-based image scrambling scheme for the generalized model of novel enhanced quantum representation (GNEQR). It is not only suit for grayscale images and color images, but also can be used in 2n× 2mimages (i.e., rectangular images). To realize the image scrambling method, we use geometric transformations and an operation of bitplane scrambling to perform position and pixel scrambling, respectively. Furthermore, the complexity of the implementation circuit of the proposed image scrambling is only O(n2) for a 2n× 2nimage. Therefore, it shows our proposed quantum image scrambling is efficient. Then, the result analysis of simulation experiments demonstrates that our proposed image scrambling is effective. In addition, security analysis shows that the proposed scrambling algorithm is secure.
Image scrambling on classical computers has been widely studied, however, the corresponding quantum algorithms are rare. This paper proposes a block-based image scrambling scheme for the generalized model of novel enhanced quantum representation (GNEQR). It is not only suit for grayscale images and color images, but also can be used in 2n× 2mimages (i.e., rectangular images). To realize the image scrambling method, we use geometric transformations and an operation of bitplane scrambling to perform position and pixel scrambling, respectively. Furthermore, the complexity of the implementation circuit of the proposed image scrambling is only O(n2) for a 2n× 2nimage. Therefore, it shows our proposed quantum image scrambling is efficient. Then, the result analysis of simulation experiments demonstrates that our proposed image scrambling is effective. In addition, security analysis shows that the proposed scrambling algorithm is secure.
Quantum image representation plays an important role in quantum image processing. In this paper, a bitplane representation of quantum images (BRQI) is proposed, which uses (n+4) or (n+6) qubits to store a grayscale or RGB color image of 2npixels. Compared with a novel enhanced quantum representation (NEQR), and a novel quantum representation of color digital images (NCQI), the storage capacity of BRQI improves 16 times and 218times, respectively. Next, some quantum operations based on BRQI are proposed, these operations including complement of colors, reverse of bitplanes, and translation of bitplanes. Analyzed the implementation circuits of these operations, the result indicates that these operations based on BRQI have lower quantum cost than NEQR and NCQI. Furthermore, an image scrambling algorithm based on BRQI is presented by combining the above operations. Simulation experiments and performance analysis show that proposed scrambling algorithm is effective and efficient.
Image scrambling is a technique used for confidential storage and transmission as well as for image information hiding. In this study, we propose a multi-channel quantum image scrambling method, which applies both color and geometric transformations of an image. This is a simple and reliable method for transforming a meaningful quantum image into a meaningless or disordered one. We performed two simulation experiments, which demonstrated the efficiency and flexibility of the proposed method. Previous studies mainly developed scrambling strategies for grayscale quantum images, whereas the proposed method is effective for the color image scrambling in the quantum computing domain.
The dual-scrambling scheme that combines position transformation and bit-plane transformation is a popular image encryption scheme. However, such schemes need more key information, and the encryption and decryption processes are complicated. In addition, the existing quantum image dual-scrambling schemes mainly deal with square images. In this paper, we propose a hybrid scrambling encryption scheme for multi-mode quantum image representation (MQIR) images based on random permutation, in which the H×W quantum image is represented in MQIR. A random number generator factor s uniquely associates one of the random permutations of integers from 1 to a positive integer, so as to hybrid scramble both the pixel position and the binarized position of each pixel value. Meanwhile, the quantum circuits and some examples of scrambling are given. Furthermore, various analyses of the performance of this scheme were conducted, including effectiveness, key space, and computational complexity. By modifying the random generation factor to construct multiple binary grayscale images, the simulated results on the IBM Quantum Cloud platform demonstrate that the proposed quantum image encryption scheme is effective. In comparison to existing quantum image dual scrambling schemes, it is both simple and effective, offering a large key space, lower computational complexity, and applicability to non-square quantum images.
Quantum processors enable real-time image processing and provide no-cloning theorem-based security for quantum image encryption. Most classical image encryption methods cannot be directly applied to quantum images due to the implementation complexity of using the quantum circuit, and most existing secure quantum image encryption methods are designed for grayscale images. Thus, we propose a quantum color image encryption method. The proposed method is designed for the existing efficient-storage quantum representation model of color digital image (QRCI) representation. The proposed QRCI-based encryption method benefits from a small number of qubits in total (i.e., 2n+7 qubits), where the QRCI representation uses 2n+6 qubits and two pseudorandom number sequences use only 1 qubit. The improved chaos-based pseudorandom number generator strikes a balance between reduced computation and security level. The two-round exclusive-OR-based diffusion method for quantum encryption significantly improves key sensitivity. Low gate costs are required. Experimental results show that the proposed method outperforms state-of-the-art quantum color image encryption methods in terms of security measures. In addition, the number of qubits of the proposed quantum image encryption method is small (2n+7 qubits).
In the digital era, characterized by extensive online data exchange, information security has become a priority. While traditional encryption methods have proven effective in protecting data transfers, the advent of advanced quantum computing has increased susceptibility to security breaches. Quantum encryption provides a revolutionary solution to this problem by using quantum mechanics principles to establish algorithms that are impermeable to decryption. Using these quantum properties, cryptographic protocols are developed to provide superior security, unlike traditional encryption methods. The image plays an important role in transmitting information in all areas. Therefore, quantum image encryption methods are specifically designed to counter the potential risks posed by quantum computers, which can compromise conventional encryption protocols. This ensures the preservation of data security despite advances in quantum computing technology. In addition, quantum image encryption improves data transmission efficiency by establishing secure communication channels using quantum stats, thereby reducing the need for bandwidth and improving transmission speed. This paper proposes a new method of quantum encryption based on GNEQR representation and the modification of pixel values and positions in an image. After converting the image into a quantum form, we applied an algorithm to modify the values and positions of the pixels using a succession of quantum gates. We concluded this study with a statistical analysis showing the robustness of our quantum image encryption method.
Abstract This paper proposes a novel dual-mode quantum image watermarking scheme based on the Generalized model of Novel Enhanced Quantum Representation (GNEQR). The scheme supports both grayscale and color images and provides two embedding modes. A key innovation is the Interleaved Tri-Symmetric Structure (ITSS) mechanism. It combines quantum image scrambling using the Quantum Baker Map (QBM) and reconstruction techniques with quantum error correction (QEC), enhancing robustness against noise and geometric attacks such as cropping and rotation. Additionally, a Quantum Parity Detection (QPD) mechanism is employed to efficiently embed and extract the watermark, substantially improving the visual quality of watermarked images. Experimental results on the USC-SIPI dataset demonstrate that the scheme achieves high visual quality, with PSNR values above 44 dB for watermarked images. Under a salt-and-pepper noise attack with density 0.05, the extracted watermark maintains a PSNR of 42 dB, outperforming the existing schemes. The proposed method also fully resists common rotation attacks and allows effective watermark extraction even when the image is cropped by 55%, confirming its strong robustness against geometric attacks. Overall, this work advances secure and efficient quantum watermarking technologies and addresses key challenges in scalability, robustness, and computational complexity for quantum image processing.