## 2 Related Work
This method also introduced a readjustment process to keep intact the stego-pixels with respective ranges; it successfully achieved the larger embedding capacity by retaining high visual imperceptibility. However, the maximum numbers of 4 LSBs are utilized during the embedding process. Another novel LSB-based technique [16] proposed is bit inversion, aimed at improving the PSNR value. In this inversion technique, certain LSBs of the cover image pixels are changed if they are matched with a particular pattern. Thus, this improved the visual quality but suffered from the low payload. Recently, another texture-adaptive (i.e., edge-based) LSB method was proposed [17]. In this method, the cover pixels are classified into edge areas and non-edge areas. The edge information is determined by the 3 most significant bits (MSBs) of the cover pixels, where the rest of 5 LSBs are adaptively employed by the LSB substitution. This method obtained high embedding capacity while retaining acceptable visual quality. However, a maximum of 5 LSBs are employed in the embedding process. Similarly, [PERSON] [18] proposed an adaptive LSB method for color images on smartphones. For all RGB channels, it proposed various LSB replacement strategies i.e., all 4 bits in each RGB channel and similarly 4 bits in R, two-2 bits in G, B channels and so on. This method achieved an average 2.8 bits per channel while it retains the high value of PSNR 43.7 dB. Its 4-bit LSB substitution strategy may employ up to 4 LSBs of each channel for embedding. On the other hand, to ensure data security, various methods employed the compression and encryption techniques to reduce the data size and increase the data security before the embedding process. For example, [PERSON] et al. [19] employed run-length encoding (RLE) to compress the secret data bits. Furthermore, it efficiently utilized the multi-bit generalized exploiting modification direction for embedding that indirectly reduces the number of modified pixels of a stego-image. This method maintained high visual quality and capacity (due to compression) but it effectively provided low embedding capacity. Similarly, [PERSON] and [PERSON] provide better data security along with imperceptibility and capacity [20]. First, the secret data is encrypted using the Advanced Encryption System (AES) algorithm and converted into four-bits fixed blocks. The LSB substitution is then performed on the basis of four bits. Although the security of data is improved the computational cost of encryption seems to be a major concern. Recently, [PERSON] et al. [21] proposed a channel indicator-based lightweight encrypted embedding method. It provides multi-level encryption for secret data and as well as stego-key. This method retains high imperceptibility and security against detectability but suffers from low embedding capacity. Most of the aforementioned recent methods are summarized in Table 1. This shows the clear picture of embedding capacity versus visual quality of existing methods. All the statistics are directly taken from the studies, where the embedding capacity depicts the average number of embedding bits per pixel (bpp). Similarly, visual quality measured in peak signal to noise ratio (PSNR) and security of undetectability is shown in the 3 rd and 4 th column. Finally, the maximum no. of LSBs (or bits) that would be modified during the embedding process of each technique is shown in the last column of the table. As can be observed in all the aforementioned LSB-based techniques; these were mainly focused on following steganography objectives, i.e., to increase the embedding capacity [8; 10; 13; 14; 15], to enhance visual imperceptibility [13; 15; 18; 23] and to improve security against detectability and hidden data [13; 14; 20; 21]. However, we found tradeoffs among all these objectives because these are correlated to one another. As we noticed (see Table 1), most of the larger capacity-based LSB methods [8; 10; 13; 14; 15; 17] employed the maximum LSBs or modify the maximum number of bits in each pixel (i.e., 3-5 bits).