# Image Watermarking between Conventional and Learning-Based Techniques: A Literature Review
## 4 Conventional Image Watermarking Schemes
### Transform Domain
#### 4.2.3 Discrete Wavelet Transform (DWT)  
This transformation decomposes an image into a low-frequency sub-band LL and three high-frequency sub-bands: LH, HH, and HL, which correspond, respectively, to the vertical, diagonal, and horizontal spatial orientations. The LL sub-bands can be further decomposed into k-levels. Therefore, one or more sub-bands of the same level or many levels can be used to embed the watermark depending on the targeted application and on the proceeded protocol. Diverse watermarking techniques developed on different levels for different purposes are presented. In [97], the authors designed a robust and invisible image watermarking scheme in the wavelet domain using the quantization technique. Here, the grayscale watermark was first decomposed into binary images ordering from least significant bit (LSB) to most significant bit (MSB). A quantization method is then used to conceal the binary bits into the carrier's wavelet coefficients. For the extraction process, a classification threshold is defined using the Otsu algorithm to extract the watermark accurately. The suggested approach achieved high imperceptibility of the watermarked image and good robustness of the extracted watermark. However, it is still sensitive to geometric attacks, as well the high processing time of the algorithm makes it difficult to use in real-time applications. The scheme in [98] introduced a robust non-blind watermarking algorithm for YCbCr color images based on channel coding. In the embedding stage, the original image was decomposed into four-level discrete wavelet transform (DWT). Then, the singular value matrices of the encoded watermark image were embedded into the Y, Cb, and Cr components of the image. For that purpose, just-noticeable distortion (JND) was used to conceal the mark in the sub-bands of the image, which provides an embedding strength. Experimentally, the scheme can achieve good transparency and robustness against various kinds of attacks. However, The coding rate of repetition code has a significant impact on the scheme's effectiveness. Furthermore, the non-blind approach is not the best option for some real-time applications. In [99], the invariant integer wavelet (IIW)-based watermarking technique was presented with a new two-level encryption algorithm. The host image is transformed into the frequency domain using the redistributed invariant integer wavelet transform (RIIWT), and QR and Singular value decomposition (SVD) are used to find the singular value of the image matrix. Afterward, The watermark is concealed in the low and high frequencies of the IIW-host image. The present scheme provides rotation stability and lowers computational cost given the use of IIW and QR decomposition tracking by SVD, respectively. Moreover, it demonstrates significant resistance to geometric attacks and standard image processing, including different filtering and cropping attacks. At the receiving part, two watermarks are obtained by inverse RI-IWT on the low-frequency sub-band. Then, the most robust watermark with a higher NC value is taken as the final watermark, However, it is worth noting that it is not practical for all applications. The wavelet-packet transform (WPT) is a type of wavelet-based transform that differs from the DWT by an increased number of filters. [PERSON] [100] came up with a robust color-image watermarking for copyright protection, which was based on WPT. Here, the multi-spectral properties of the primary color components of the RGB image are chosen due to their simplicity and high color channel correlation. First, a scrambled watermark is generated by applying the chaos-encryption unit followed by the Arnold transform, which enhances the level of security. Then, after the transformation of the host image using the WPT, the vector information of the transformed image is used to compute the threshold values, which are used to select the embedding place of the watermark. In this sense, the safe locations depend on the inter-layer energy of the wavelet-packets coefficients.