## 1 Introduction  
Steganography is the science that deals with providing confidentiality using obscurity. The secret data are sent to the receiver by hiding their existence within another \"innocent\" host signal. The output at the sender side is a semi-identical signal to the original host signal and contains the secret data. This signal is named as the carrier signal. Steganography is popular and is preferable by some developers over encryption techniques for the obscurity nature of the communication [1]. Encryption techniques operate by transforming the secret data into an inapprehensible form. This form creates suspiciousness and an eavesdropper can expect the secrecy of the communication. However, a steganography technique does not keep a trace since a secret message is hidden in an \"innocent\" host signal, which does not trigger the attention of an eavesdropper. With the current advancements in the processing speed of shared networks such as the internet, official entities are using such public networks to send confidential data. Therefore, the need to secure confidential messages over public networks has become a top research area in the last few years [2, 3, 4, 5]. Hiding capacity, imperceptibility, robustness, and security are the four main attributes of steganography. Hiding capacity is the amount of hidden secret data compared to the size of the host signal. Imperceptibility refers to the degree of similarity between the host and carrier signal. The robustness aspect refers to the ability of the secret data to withstand attacks. The fourth attribute, the security attribute, deals with the obscurity level and the ability to prevent an eavesdropper from discovering the secrecy of the communication. Developers aim to develop steganography techniques that improve some or all of the four attributes. However, improving some attributes simultaneously is not a trivial process as some attributes such as the hiding capacity and the imperceptibility attributes are opposing each other. The attempt to increase the amount of hidden data will naturally affect the quality of the carrier signal. That is true since hiding is usually performed by replacing some of the original data of the host signal with the secret bits. Therefore, the more data to be hidden, the more original data to be destroyed, which results in higher distortion in the carrier signal. The capacity-quality trade-off is inherently a limitation in steganography, as the ideal scenario--achieving infinite hiding capacity with zero quality degradation--is not possible in practice. This trade-off reflects a negative phenomenon, as increasing the amount of hidden data typically results in more significant degradation of the stego signal's quality. While efforts can be made to minimize the impact on quality, the trade-off remains a fundamental challenge in balancing the goals of maximizing capacity and preserving the integrity of the carrier signal [6]. For images, low hiding capacity simply means sending low-resolution secret images which can be unacceptable for critical confidential communications. Therefore, it is important to find a solution to increase the hiding capacity without compromising the quality of the carrier image. A common approach to hiding confidential data involves replacing the less significant bits of the host signal with the secret bits. By adopting such an approach, it is possible to hide a significant amount of secret data while maintaining the quality of the carrier signal. The challenging issue is the process of figuring out these less significant bits and whether destroying these bits would significantly damage the quality of the carrier signal. There are two approaches to finding the less significant bits. The first approach is biological and based on the abilities of the human visual system. It is known that the human visual system is less sensitive to noise distributed in high-frequency areas of an image such as edges.