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.
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.
To address the problem that existing quantum image watermarking schemes have only a single watermarking mode with weak robustness, in this paper we propose a novel multi-modal quantum watermarking (MMQW) scheme using the generalized model of novel enhanced quantum representation. Our scheme provides four quantum watermarking modes (G_G, G_C, C_C, C_G), covering both types of grayscale and color images for the watermark and the carrier image. To enhance the robustness, we propose the Block Bit-plane Centrosymmetric Expansion (BBCE) method, which utilizes controlled quantum gates to extend the watermark, making our method resistant to noise and geometric attacks. Moreover, we propose a Brightness-based Watermarking Mechanism (BWM) for embedding and extraction. By uniform embedding, BWM not only minimizes the impact on the carrier image but also reduces the visual distortion of the extracted watermark. In the proposed MMQW, we implement three adaptive embedding strategies using controlled quantum gates, each of which is adaptively triggered according to the corresponding modalities. Detailed quantum circuits for quantum computing are provided. To evaluate imperceptibility and robustness of the MMQW, we conduct experiments using high-resolution images from the USC-SIPI dataset. The results show that PSNR of the watermarked image ranges from 36 dB to 56 dB, indicating the high visual quality. The PSNR of the extracted watermark is about 34 dB when the noise density is 0.05, while the PSNR is higher than 48 dB under common quantum rotation attacks, which indicate the high robustness against noise addition and geometric attacks. In addition, the proposed MMQW can resist to cropping attack with cropping percentage up to 55%. A comprehensive comparison with existing state-of-the-art works shows that our method has significant advantages.
This paper proposes a novel geometrically invariant quantum watermarking scheme using Quantum Error Correction (QEC) and Novel Enhanced Quantum Image Representation (NEQR). The Geometric Transformation-based Image Assembling (GTA) mechanism is proposed to reconstruct the quantum watermark image utilizing QEC principle. The proposed GTA mechanism involves Quantum Image Rotation (QIR) and Quantum Block Rotation (QBR), thus two corresponding quantum watermarking methods, GTA_QIR and GTA_QBR, are proposed and detailed quantum circuits with complexity O(n) are designed. Then the Quantum Majority Finder (QMF) is proposed for embedding the watermark uniformly. In the experiments, we employ dataset USC-SIPI to evaluate the visual quality and robustness of the proposed scheme. Comparisons with the recent quantum watermarking methods is conducted and the results show that our methods have a superior performance. When under attack of ’Salt and Pepper’ noise addition, the proposed GTA_QIR and GTA_QBR improve the average Peak Signal-to-Noise Ratio (PSNR) by 22.57% and 23.49% at a density of 0.05, while at a density of 0.1, the average improvement is 11.13% and 12.05% respectively. Moreover, to the best of our knowledge, this is one of the first quantum watermarking scheme which demonstrates resistance to geometric attacks.
Quantum watermarking can be used for image ownership protection. This paper proposes a quantum watermarking scheme based on Novel Enhanced Quantum Representation (NEQR), DNA encoding, and quantum error correction (QEC). First, XOR operations are performed between the watermark image and a DNA key sequence. Then, performing DNA addition between the resulting image and DNA key image, the encrypted watermark image is obtained. Using the quantum parity determination (QPD) method, the encrypted quantum watermark image is embedded into the least significant bit (LSB) of the carrier image. The quantum circuits for the scheme are also provided. In order to evaluate the effect of the scheme, the watermarking scheme is simulated using MATLAB. The simulation results show that the embedded watermark has good visual quality, and the PSNR of watermarked image is about 51 dB. When ‘salt and pepper’ noise with a density of 0.10 is added to the watermarked image, the PSNR for extracted watermark is 20.38 dB. When the cropping proportion is 50%, the PSNR for extracted watermark is 22.08 dB. These results indicate that the proposed watermarking scheme has strong robustness against noise and cropping attacks. The extraction of watermark is also simulated for cases where the DNA key sequence or key image is damaged. If there is a small amount of damage to DNA key sequence or key image, the watermark cannot be extracted effectively. The watermark encryption further increases the difficulty of unauthorized watermark extraction. Applying DNA encoding to quantum watermarking research also offers significant novelty.
Quantum watermarking technology embeds invisible watermark images into carrier images to mark ownership, which has broad application prospects. In the paper, with using the novel enhanced quantum representation (NEQR) of the image, a quantum watermarking scheme based on a novel space geometric transformation and Fibonacci scrambling is proposed. Combined with the Quantum Majority Finder (QMF) method, the watermark information is embedded into various positions of the carrier image. The Fibonacci scrambling disperses the pixel information of the watermark image into the entire image range, and the space geometric transformation rearranges the individual watermark pixel information. These methods improve the robustness and security of watermarked images against noise and cropping attacks and ensure the watermark's visual invisibility. Applying simulation experiments, these quantum processes are implemented on a classical computer. The visual quality quantified by Peak Signal-to-Noise Ratio (PSNR) and robustness of the proposed method are analyzed. Our watermarking scheme has good visual quality, and the PSNR of the watermarked image is approximately 45. Compared to existing methods, our scheme exhibits robustness to resist noise and cropping attacks. Especially in large-scale cropping, the proposed scheme has excellent advantage. Experiment results verify the effectiveness and superiority of the proposed scheme and provide new ideas and methods for developing quantum watermarking technology.
Abstract Quantum image processing, which merges classical image processing techniques with quantum computing, provides exceptional storage capacity and unparalleled parallel computing power. In this study, we present a quantum color image watermarking scheme that employs quantum error correction codes to address issues such as pixel loss and image distortion during watermark embedding and extraction. By utilizing the least significant bit method to embed the color values of the watermark image into those of the carrier image, we improve the scheme’s robustness. We also address the error correction capabilities of channel coding for phase-flip errors and follow the majority principle, resulting in more accurate extraction of the watermark image’s color and enhancing the watermarking scheme’s reliability and integrity. Our experimental simulations demonstrate that the proposed watermarking scheme boasts high security, strong robustness, and excellent concealment.
The protection of multimedia information against copying and tampering attacks by unauthorized parties is a challenge nowadays because of the tremendous increase in digital communications. Based on this, this paper presents a quantum blind image watermarking scheme incorporating Improved Novel Enhanced Representation (INEQR) for efficient image encoding, two-dimensional Quantum Discrete Cosine Transform (QDCT) frequency domain processing, and adaptive QIM for watermark embedding. The selection of watermarking parameters in this framework is carried out in a completely secure manner using Quantum Key Distribution (QKD) based on BB84. Simulation work on 30 standard grayscale images shows the strong imperceptibility, achieving PSNR values in the range of 52–58 dB and SSIM values between 0.98 and 0.999. and a more than 95 percent accuracy level in watermark recovery under attacks such as noise, compression attacks, and geometric attacks, thus authenticating PSNR-52– 58 dB and SSIM-0.98–0.999. Robustness analysis performed against signal processing and geometric attacks indicates reliable extraction of watermarks, where the proposed framework attains an extraction accuracy of more than 95% under additive noise and filtering scenarios and moderate robustness against geometric attacks such as rotation and scaling. These indicate that the proposed framework is effective and provides imperceptible blind image watermarks based on the quantum approach.