Digital watermarking technology has become an important means to protect the copyright of digital media. However, existing methods often fail to simultaneously meet the key requirements of high real-time performance, high invisibility, strong robustness, and enhanced security. To overcome this limitation, we propose an efficient digital watermark embedding and extraction method based on an invertible matrix fusion domain, which establishes a balanced trade-off among these competing objectives. This method, for the first time, derives the properties of invertible matrix multiplication in the spatial domain and embeds the watermark by directly calculating the high-energy coefficients and evenly distributing the changes, thereby simplifying the embedding process and improving computational efficiency. To address the error propagation problem in quaternary coding, a minimum error propagation strategy based on quaternary (MEPQ) is proposed to enhance the robustness. In addition, the watermark image is encrypted by using the four-dimensional Lorenz chaotic system, which expands the key space and resists statistical attacks. Experimental results demonstrate the superior performance of the proposed method: it achieves excellent invisibility (PSNR$\gt 40$$dB$, SSIM$\gt 0.98$), strong robustness against various attacks (average NC$\gt 0.98$), high real-time efficiency (embedding time 0.18 seconds, extraction time 0.06 seconds, with$O(n)$complexity), and enhanced security with a large key space ($2^{768}$) to resist statistical attack and brute-force attack. These comprehensive results confirm that our method successfully meets the combined demands of real-time processing, invisibility, robustness, and security.

In view of the fact that many watermarking schemes cannot well adapt to the occasion of image copyright protection with a large amount of information, and the copyright protection of color image is facing severe challenges, a dual-color image watermarking scheme based on URV decomposition (URVD) and image correction is designed in this paper. The two-dimensional Logistic-adjusted-Sine map is first used to generate two chaotic sequences for pixel-level scrambling and bit-level diffusion of the watermark image, and URVD is applied to watermarking scheme. After fully considering the relationship between image channels, the watermark is embedded into the maximum URVD coefficient by using quantization index modulation based on variable quantization steps. The greatest contribution of this paper is to propose a new image correction algorithm as a pretreatment of watermark extraction, which mainly includes fast detection of feature points, image correction, and sawtooth processing, and it solves some problems existing in image correction algorithms based on geometric characteristics. Experimental results show that the proposed scheme has good invisibility, strong robustness, and high security. Compared with existing schemes, the proposed scheme has better performance under the same actual embedding rate, especially stronger and more effective robustness against some common geometric attacks.

It has great significance for protecting the image copyright with color image digital watermarking technique, which needs the watermarking algorithm has high robustness, good imperceptibility and short running-time. A blind colour image watermarking algorithm combined spatial domain and singular value decomposition (SVD) is designed to protect the rightful ownership of color image in this paper. The theoretical principle combined SVD and spatial domain is first discussed and proposed in this paper. Based on the derived principle, the watermark information can be directly embedded into the maximum singular value (MSV) of the host image in the spatial domain by the new quantization index modulation with variable quantization step, and the embedded watermark information can be directly extracted from the MSV of the watermarked image block in the spatial domain with geometrical correction. The contributions of this paper include the following four points: (1) the relationship between the changed MSV of SVD and the average changed value of image pixel in the spatial domain is the first derived in this paper; (2) the presented method has the merits of both spatial-domain technique and transform-domain technique; (3) the relationships of each component of the color image are used to improve the invisibility and the geometrical correction of watermarked image is also adapted to further improve the robustness; and (4) this presented method overcomes the false-positive problem that existed in many watermarking methods based on SVD. Simulation results demonstrate the new presented color image watermarking technique has better imperceptibility, higher robustness and shorter running-time compared with some state-of-the-art methods.

In this paper, a spatial domain-based blind watermarking scheme of color images integrating multilevel discrete Hartley transform (DHT) is proposed to protect color digital images' copyright under the current 5G network environment. On the basis of the unique spatial computing property of the maximum energy coefficient of DHT and the energy aggregation principle of multilevel image transform, the color watermark image scrambled by Affine transform is directly hidden into color carrier image by quantitative techniques in the spatial domain, rather than the complex DHT domain. The specific performance of the scheme in various aspects is as follows: (1) the average value of the peak signal-to-noise ratio is higher than 40 dB; (2) the average value of structural similarity index metric remains above 0.9700; (3) the average value of normalized cross-correlation under no attack is 1.0000; (4) the average value of normalized cross-correlation. under attack is above 0.9600; (5) the total execution time is 1.1856 s; (6) the maximum embedding capacity is 0.0625 bpp; and (7) the entire key space is greater than 2432. Multiple simulation results demonstrate that the proposed scheme is not merely imperceptible and robust, but also secure and efficient, which can protect the digital copyright with effect.

To solve the copyright protection problem of a colour image, a new blind colour image watermarking method combining a discrete cosine transform (DCT) in the spatial domain is presented in this study. The advantages of the spatial‐domain watermarking algorithm and frequency‐domain one are made full use in this scheme. Based on the different quantisation steps in red, green, and blue three‐layer images, the processes of watermark embedding and blind extraction are completed in the spatial domain without a real DCT domain. The scheme is realised by using the unique features of the direct current (DC) coefficient and the relativity of DC coefficients between adjacent pixel blocks. This scheme can effectively solve the problems of the large‐capacity colour image watermarking algorithm, such as long‐running time and weak robustness. Comparing with other advanced watermarking algorithms, the presented scheme has better invisibility, stronger robustness, and higher real‐time performance.

In this study, a novel blind image watermarking technique using Hessenberg decomposition is proposed to embed colour watermark image into colour host image. In the process of embedding watermark, the watermark information of colour image is embedded into the second row of the second column element and the third row of the second column element in the orthogonal matrix obtained by Hessenberg decomposition. In the process of extracting watermark, neither the original host image nor the original watermark image is needed and it is impossible to retrieve them without the authorised keys. Experimental results show that the proposed colour image watermarking technique based on Hessenberg decomposition outperforms other watermarking methods and it is robust to resist a wide range of attacks, e.g. image compression, filtering, cropping, rotation, adding noise, blurring, scaling, sharpening and rotation and so on. Especially, the proposed method has lower computational complexity than other methods based on singular value decomposition or QR decomposition.