# Image Watermarking between Conventional and Learning-Based Techniques: A Literature Review
## 4 Conventional Image Watermarking Schemes
### Transform Domain  
Usually, spatial watermarking techniques can be easily manipulated; therefore, these techniques are too fragile and less robust to different types of attacks compared with transform domain algorithms. These shortcomings have led to the search for transform domain watermarking techniques that successfully hide data in the frequency coefficients of the transformed image, rather than the spatial domain [77]. Watermarking methods in the frequency domain convert an image from the spatial/temporal domain to another domain using a pre-defined transform. Then, the watermark is inserted into the selected coefficients of the transformed image [78]. Finally, the inverse transformation is performed to retrieve the watermarked image. Figure 8 shows the steps of image watermarking in the transform domain. Digital watermarking algorithms designed to work in a transformed domain are more robust and complex; however, they are extensively employed [79]. Regarding frequency transformations, including the discrete cosine transform (DCT), discrete Fourier transform (DFT), discrete wavelet transform (DWT), and singular value decomposition (SVD), among others, the energy of the signal is concentrated in the low-frequency components. The insertion of a mark in these frequencies provides good robustness; however, it introduces apparent distortions in the spatial/temporal domain [80]. On the other hand, insertion in the high-frequency components does not degrade the signal quality but makes the mark vulnerable to attacks, such as low-pass filtering and compression. Therefore, the mid-frequency band is generally the best choice for watermarking, since it fits the requirement of compromise between robustness and invisibility. Several studies on image watermarking based on the transform domain have been carried out, showing good robustness, imperceptibility, and security to different attacks, such as image-processing attacks and geometric transformations. This section reviews the most recent of these studies that primarily use frequency domain transforms, such as DCT, DFT, and DWT.  
\begin{table}
\begin{tabular}{p{42.7 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Reference Approaches** & **Objectives** & \begin{tabular}{c} **Cover/** \\ **Watermark** \\ **Size** \\ \end{tabular} & \
\begin{tabular}{c} **Evaluation** \\ **Metric** \\ \end{tabular} &
\begin{tabular}{c} **Advantages and Weaknesses** \\ \end{tabular} \\ \hline
[70] & \begin{tabular}{c} Invariant \\ significant \\ bitplane \\ probability \\ density \\ \end{tabular} & \begin{tabular}{c} Robustness against desynchronization attacks \\ \end{tabular} & \begin{tabular}{c} 512 \(\times\) 512 \\ pseudo-random \\ sequence of \\ 85 bits \\ \end{tabular} & \
\begin{tabular}{c} 512 \(\times\) 512 \\ PSNR, \\ MSE, \\ SSIM \\ \end{tabular} &
\begin{tabular}{c} + Resistance to common image-processing \\ attacks and desynchronization attacks \\ - High computational complexity \\ - Less robust against JPEG compression \\ and scaling \\ \end{tabular} \\ \hline
[73] & LSB, ISB & \begin{tabular}{c} Tamper detection and localization of medical/general images \\ \end{tabular} & \begin{tabular}{c} 256 \(\times\) 256 \\ 64 \(\times\) 64 \\ \end{tabular} & \
\begin{tabular}{c} PSNR, \\ SSIM, \\ BER \\ \end{tabular} &
\begin{tabular}{c} + Low complexity \\ + Highly visual image \\ - Fragile \\ - Lack of irreversibility \\ \end{tabular} \\ \hline
[74] & \begin{tabular}{c} LSB substitution mechanism \\ \end{tabular} & \begin{tabular}{c} Enhance the conventional LSB technique of digital image watermarking \\ \end{tabular} & \
\begin{tabular}{c} 700 \(\times\) 700 \\ 100 \(\times\) 100 \\ \end{tabular} &
\begin{tabular}{c} PSNR, \\ NCC \\ - Less robust against median filtering and \\ speckle noise \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table}
Table 1: Summary of spatial domain-based image watermarking techniques.