# High-Fidelity Steganography: A Covert Parity Bit Model-Based Approach
## 4 Proposed Scheme
### Data Embedding
The level of correlation between the pixels was used as the measure to classify images as low-correlated, mid-correlated, or highly-correlated content in terms of the inter-pixel correlation level. The last image, \"Rose\", was used as the secret image in the experiments. This section follows the strategy of an ablation study to evaluate the performance of the proposed technique. An ablation study is a crucial experimental approach used to assess the contribution of individual components within a system or algor

Figure 6: The first three images are used as cover images in our experiments: (**a**) Airplane, (**b**) Animal, (**c**) Vegetables while the final “Rose” image (**d**) is the secret image [22]. removing or altering specific elements, researchers can evaluate the impact on overall performance and functionality. This method helps to identify which components are essential, which are redundant, and how the different parts interact with one another. In the context of the proposed steganography technique, an ablation study was conducted to isolate the effects of various algorithm modifications, such as changes in polynomial degree and scaling factor values. The results of this study not only highlight the strengths of the proposed approach but also provide valuable insights into areas for further optimization and refinement. Capacity-Transparency Analysis

The bit-per-pixel (_bpp_) metric is utilized to calculate the capacity ratio. The _bpp_ ratio is computed using

\[Capacity\ (bpp)=\frac{s}{c}\times r, \tag{6}\]

where \(s\) is the total number of secret pixels, \(c\) is the total number of cover pixels, and \(r\) is the total number of bits per pixel. In the following experiments, \(r\) was equal to 24, as the cover images were colored images with the three color channels (red, green, and blue) and each pixel in each channel was coded using 8 bits. Stego quality is determined using the Peak Signal-To-Noise Ratio (PSNR) and the Structural Similarity Index (SSIM) [5]. First, the performance of the proposed hiding strategy was examined against the coefficient replacement hiding strategy adopted by various DCT schemes, which is the simple replacement of the high-frequency DCT signal with the scaled-down secret pixels. Tables 1 and 2 show a comparison when hiding with polynomial degrees \(n\) of 2 and 15, respectively. These results show that the proposed strategy outperforms the coefficient replacement embedding strategy in all cases. Moreover, the proposed strategy achieves promising results even when hiding a large amount of confidential bits. For example, the proposed steganography technique obtained PSNR values of 30.22 dB and 32.92 dB when embedding with 22.89 bpp when using polynomial degrees \(n\) of 2 and 15, respectively. Another fact that can be extracted from Tables 1 and 2 is that increasing the polynomial degree improves the quality of the stego image. That is because increasing the polynomial degree enhances the modeling process and produces a closer signal to the original high-frequency DCT signal. However, this improvement in stego quality increases the communication cost between the sender and receiver. The reason for this is that more polynomial coefficients need to be sent to the receiver in order to provide a recoverable secret image. The reason for selecting a polynomial degree of \(n=2\) in the experiments was to show the results obtained with the lowest possible polynomial degree, as \(n=1\) will generate a linear function \((p_{1}x+p_{2})\) that cannot model DCT signals. Even when using the lowest polynomial modeling degree, the proposed scheme was able to outperform the coefficient replacement strategy and achieve outstanding results in terms of the hiding capacity, which reached up to 22.89 bpp while generating a stego image with a quality of 30.22 dB.