## 2 Related Work
Later, pair-wise prediction error and machine learning-based prediction approaches were widely studied to improve the embedding rate [30; 31; 32]. Difference expansion is another major approach exploited for RDH in natural images and medical images [33]. This scheme is also concerned with overflow or underflow issues. An additional location map is required to handle overflow and underflow to ensure the lossless recovery of the original image. The well-known difference expansion RDH schemes are available in [34; 35; 36]. A RDH scheme capable of providing high embedding capacity through an image scaling approach is discussed in [37]. In this approach, the original image of size \(N\times N\) pixels is scaled up to a size of \(2N\times 2N\). The new pixels are introduced in the scaled-up image by replicating the pixels. The newly introduced pixel through the pixel-to-block conversion process is used to embed the clinical data and the additional authentication details for tamper detection. In every block of size \(2\times 2\) pixels, every pixel except one pixel (pixel at the location (0, 0)) is used for embedding. The system claimed a high embedding rate, but the primary concern is that the bandwidth requirement for transmission is four times greater than the bandwidth requirement for transmitting the original image. However, the scheme allows a concealed transmission of clinical data and the medical image. The scheme discussed in [37] was considered for further study by researchers in 2021, and an extended version was proposed in [38]. This paper discussed a scheme that can facilitate patient report transmission along with tamper detection capability. An authentication code is generated from the medical image, and the same is embedded in the image for tamper detection. Similar to the scheme discussed in [37], the original image of size \(N\times N\) pixels is scaled up to a size of \(N\times N\). The new pixels in the scaled-up image are estimated based on a set of new predefined rules, which helps obtain scaled-up (watermarked) images with better visual quality. The readers may note that the key concern of the scheme [37] remains in the scheme reported in [38]. A Reed-Solomon code-based RDH scheme was introduced in [39]. The key benefit of the scheme discussed here is the resistance of the data-hiding scheme against salt and pepper noise. This scheme also ensures a high-quality stego image after performing data hiding. An improved chaos encryption (ICE)-based approach was introduced in [40] to improve the security and the quality of the stego image. An enhanced modified signed digit (EMSD) and least significant substitution-based algorithm were discussed in [41]. This scheme ensures a high embedding rate, low computational complexity and high visual quality. Since this is a hybrid approach, steganalysis and decoding of the secret message is quite difficult in this approach. The literature review in this domain led us to the following conclusion:  
* The embedding capacity is a major concern in the RDH domain, and all researchers are working towards this. Note that lossless recovery of the original image and the message extraction should not be compromised while achieving a better embedding rate. * An image scaling-based approach is not a good solution for the RDH since it leads to high bandwidth requirements and storage space that we do not want to entertain. * The histogram-based RDH schemes and difference expansion-based RDH schemes need to consider the location maps to ensure lossless recovery due to overflow and underflow. * The RDH schemes should be lightweight enough to provide real-time performance during data hiding and image recovery. All the points mentioned above were kept in mind while proposing a new bit plane compression-based RDH scheme with the modified Elias gamma encoding approach.