# Quantum Image Steganography Schemes for Data Hiding: A Survey
## 4 Discussion
Additionally, higher imperceptibility and embedding capacity are also perceived in the spatial domain. In our survey paper, multiple approaches following the map domain class were discussed including the least significant qubit, turtle-shell-based matrix, inverted pattern approach, pixel value differencing, EMD, and interpolation-based scheme. The spatial domain has included many representations and has shown improvements in quantum image steganography, making it a popular domain in the quantum-steganography field. An example is [PERSON] et al. [6], who used the least significant qubit technique that resulted in a reduction in the time complexity of the algorithm by directly embedding the covert message's qubits into the least significant qubit of the carrier image. Moreover, as the experiments of [PERSON] et al. [6] showed, using the NEQR model [7] and a novel LSB embedding scheme, results in a large increase in performance speed. [PERSON] et al. [15] used the turtle-shell-based matrix technique which showed an increase in security by utilizing an algorithm that added an error detection code called a parity bit at the end of each binary sequence, ultimately achieving a better trade off between image quality and embedding capacity. In the spatial domain, the least significant qubit (LSBq) is considered the most popular out of the rest of the approaches and is widely known for its easy implementation and low time complexity [45]. However, it can also be deemed as the weakest in performance compared to others due to its low robustness and security. For this reason, we have seen multiple authors such as [PERSON] and [PERSON] et al. improve the scheme by applying changes to its structure and adding elements that could improve the scheme's vulnerable spots. We have also seen many approaches that use LSB and LSBq in their algorithm but only as a supporting part. For instance, the inverted pattern approach by [PERSON] et al. used the inverted pattern scheme along with LSB to increase the image's quality and imperceptibility by comparing each pixel of the embedded image along with an inverted version of it to find the best sequence out of the two and use it to produce the final image. In addition to that, there were improvements shown in the inverted pattern approach technique by [PERSON] et al. [9], who were the first to use LSB to hide the secret message content into an NQER image model and achieve a lower computational complexity and superiority in visual quality and capacity. We have also explored the pixel value differencing approach used in quantum contexts, which is also considered as a type of spatial domain. [PERSON] et al. [9] accomplished superior spatial visual recognition as well as high payload [31] using the pixel value differencing technique that utilizes a good steganographic algorithm. Furthermore, [PERSON] et al. [12] found a way to reach an excellent embedding capacity without affecting the image quality with an approach in which embedding confidential messages into an NEQR model image was performed using image interpolation; the approach is known as the interpolation-based scheme. One of the disadvantages of using the spacial domain is its vulnerability to attacks, as it does not have as much security as the transform domain. For the transform domain, an advantage of it is its high protection against compression and geometric assaults. However, the disadvantages shown in the transform domain are its high complexity, limitation of space for embedding images, and its overall lower perceptible controllability. One of the approaches presented in this paper that relates to the transform domain is [PERSON] et al. [10]'s scheme, which has reached good visual quality, resistance to data loss hazards, as well as high embedding capacity, and strong security by using the controlled alternate quantum walks protocol.