# Image Watermarking between Conventional and Learning-Based Techniques: A Literature Review
## 4 Conventional Image Watermarking Schemes
### Hybrid Domain
In [106], a blind medical-image watermarking scheme was designed using hybrid transforms, DWT, and Schur decomposition. In order to achieve both tamper recognition and authenticity, dual watermarks were concealed in the region of the non-interest (RONI) blocks of the images. To determine the embedding position, the discrete wavelet transform and the Schur decomposition are then performed. Both watermarks are compressed by Lempel-Ziv-Welch (LZW) to increase the payload capacity according to image quality, while the swarm bacterial foraging optimization algorithm (PSBFO) is used to achieve the balance between imperceptibility and robustness. Evaluations carried out demonstrated the performance of the watermarking algorithm in terms of imperceptibility and robustness against various attacks. However, since the scheme consists of several mechanisms, as the file size increases, so does the complexity. For the same purpose, [PERSON] et al. [107] presented a hybrid watermarking scheme intended for the medical field that relies on three collective strategies, including DWT, DCT, and SVD. The region of interest (ROI) and region of non-interest (RONI) are generated from image separation, and the DWT is applied toRONI to produce low- and high-level bands. After the selection of embedding potential blocks using the human visual system (HVS), and the subdivision of these blocks to carrier matrices, the watermark is inserted by modifying the largest diagonal singular values of these matrices. The technique is blind and achieves higher imperceptibility, as well as robustness. However, the combination of these three transformations increases the computational complexity and the risk of false positives. In [108], a robust rotation-invariant watermarking technique is suggested. In this approach, DWT is performed on the original image, and the DWT-LL sub-band was chosen for embedding. After dividing the LL sub-band into non-overlapping blocks, DCT is performed on random blocks. Then, the singular value matrix of the watermark is concealed in the DCT coefficients. Hence, using singular value decomposition improves the robustness of the watermarking scheme against rotation attacks, while the use of DWT and DCT transforms help to strengthen robustness against common image-processing attacks, such as noise, blurring, and compression. In this case, the security of the system was not considered since no encryption techniques were used to encrypt the watermark. Recently, [PERSON] et al. [109] proposed an improved image watermarking method based on DWT-DCT coefficients. The image blocks with the highest variance values are selected for watermark embedding, which is less sensitive to the human eyes. DWT is applied on these blocks to produce a DWT LL sub-band followed by a two-dimensional DCT. Afterward, a set of embedding rules are used to conceal the watermark, considering the adaptive scaling factor. Additionally, the \(x\) and \(y\) coordinates of the selected image blocks are adopted for extracting references. In this work, the imperceptibility of the watermark image was verified and the robustness against various attacks was proved, including compression, Gaussian filter, and sharpening. However, the quality of the watermarked image and the robustness against added noise can be improved. The main idea of the hybrid domain is to combine the characteristics of several domains and adopt them in one method to improve performance and reduce the weakness of the watermarking schemes. On the other hand, this methodology increases computational complexity in some cases. Table 3 summarizes an overview of the hybrid domain-based state-of-the-art schemes.