## 2 Related Work  
This section is intended to give a brief literature review of LSB-based image steganography techniques since the proposed method is based on LSB substitution. Usually, in LSB-based methods, the secret data bits are substituted in \(k\)-least significant bits of each pixel. In the literature, various types of LSB-based techniques have been proposed [7; 8; 9; 10; 11; 12; 13; 14; 15; 16; 17; 18; 19; 20; 21; 22; 23] targeted at high capacity, visual quality and security. One of the earliest adaptive LSB-based methods was introduced by [PERSON] et al. [7]. This method exploited the brightness, edges, and texture of the cover image to determine the number of \(k\) LSBs for data embedding. The higher value of \(k\) depends on the noise non-sensitive regions. Furthermore, an optimal pixel adjustment process is employed to enhance the visual quality. To obtain a larger embedding capacity, [PERSON] et al. [8] proposed a method employing an adaptive LSB substitution for data embedding based on edge computation. A maximum of 4 LSBs are utilized during the embedding process. This method improved the embedding capacity but suffered from low visual imperceptibility (PSNR \(<\) 35 dB). [PERSON] and [PERSON] [9] proposed a semi-reversible data hiding technique involving interpolation and LSB substitution. The interpolation methods are used to scale up and scale down the cover image, where the LSB substitution (up to 3 LSBs) is employed for embedding. This method provides the larger embedding capacity while maintaining acceptable visual quality. However, this method did not discuss any security evaluation. [PERSON] and [PERSON] [10] also employed the LSB substitution technique by dividing the image into two parts, one for embedding data and the other for indicating the embedding changes. This method increases the embedding capacity and improves the visual quality of the stego image, while the number of LSB substitutions is adaptive,ranging from 1-5. The visual quality of this method directly depends on the number of utilized LSBs. As the number of LSB substitutions increases, the visual quality of the stego-image decreases. To further enhance the embedding capacity, researchers combined the other existing methods with the LSB technique. For example, [PERSON] et al. [11] proposed a larger embedding capacity based on LSB with the pixel value difference (PVD) [12] based method. The average difference value of the four-pixel block is used to classify the high and low texture pixels block. Furthermore, the secret data are embedded using _k_-bit modified LSB substitution. Similarly, [PERSON] et al. [13] integrated the LSB substitution with a PVD method. This method divides the image into 2 \(\times\) 2 pixel blocks and applies _k_-bit LSB in the upper left pixel of the block. Next, a PVD embedding process is applied to the base (upper-left) pixel with the remaining pixels of the block. This method provides the larger embedding capacity with the improved PSNR value. However, the _k_-bits ranges are from 1 to 3, indirectly indicating that up to 3 LSBs of a pixel can be modified during the embedding process. In [14], [PERSON] et al. proposed a recursive hybrid approach of LSB with other existing PVD and modification of prediction error (MPE) methods. First, it classified the lower and higher texture of an image; then it employed the LSB substitution and PVD methods. Next, to enhance the embedding capacity it recursively employed the PVD shift and MPE. This method provides larger capacity with acceptable PSNR. However, up to 4 LSBs are utilized for the embedding process. Similarly, [PERSON] et al. [15] introduced adaptive LSB embedding by utilizing the PVD characteristics. This method divides the cover image into two-pixel blocks, further computing the difference in value between the two pixels. The numbers of secret bits are estimated based on the computed difference value. Next, the adaptive LSB scheme is employed to embed the number of secret data bits inside the selected pixel blocks.