# Hyperspectral Data: Efficient and Secure Transmission
## 2 An Efficient and Secure Transmission Framework
### An Effective Implementation of the Proposed Framework
#### 2.1.1 Reversible Invisible Watermarking Scheme for Hyperspectral Images
\begin{table}
\begin{tabular}{l c c c c} \hline \hline
**Scenes** & **Cuprite** & **Jasper Ridge** & **Low Altitude** & **Lunar Lake** & **Moffett Field** \\ \hline Scene 01 & 121.18 & 119.88 & 119.96 & 121.85 & 120.12 \\ Scene 02 & 119.91 & 120.37 & 119.72 & 121.77 & 122.18 \\ Scene 03 & 121.23 & 119.06 & 120.60 & 121.26 & 123.93 \\ Scene 04 & 121.44 & 119.09 & 120.63 & - & 120.24 \\ Scene 05 & 121.76 & 119.54 & 120.50 & - & - \\ Scene 06 & - & / & 120.75 & - & - \\ Scene 07 & - & - & 120.14 & - & - \\ Scene 08 & - & - & 119.77 & - & - \\ Average & 121.10 & 119.59 & 120.26 & 121.63 & 121.62 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Achieved results in terms of PSNR, by embedding \(w_{2}\) (Dataset 1). Notice that by “/”, we refer to the fact that the algorithm failed the embedding process (due to the limited dimensions of the hyperspectral image). \begin{table}
\begin{tabular}{l c c c c c} \hline \hline
**Scenes** & **Cuprite** & **Jasper Ridge** & **Low Altitude** & **Lunar Lake** & **Moffett Field** \\ \hline Scene 01 & 124.45 & 123.21 & 123.40 & 125.21 & 123.34 \\ Scene 02 & 123.03 & 123.28 & 122.89 & 125.13 & 125.32 \\ Scene 03 & 124.36 & 122.45 & 124.11 & 124.27 & 127.09 \\ Scene 04 & 124.58 & 122.41 & 123.75 & - & 123.28 \\ Scene 05 & 124.83 & 122.81

#### 3.2.2 Simulation Results on the Dataset 2

In Tables 5 and 6, the achieved simulation results are reported, in terms of the PSNR metric by embedding the watermark \(w_{1}\) and the watermark \(w_{2}\), respectively. The value assumed by the PSNR metric is reported for each scene (first column) of the Yellowstone calibrated (on the second column) and uncalibrated (on the third column), Hawaii (on the fourth column), and Maine (on the sixth column) hyperspectral images. Figure 3 reports the average PSNR results we have achieved by embedding the watermark \(w_{1}\) (columns in red) and the watermark \(w_{2}\) (columns in blue), by considering Dataset 2. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scenes** & **Yellowstone (Calibrated)** & **Yellowstone (Uncalibrated)** & **Hawaii (Uncalibrated)** & **Maine (Uncalibrated)** \\ \hline Scene 00 & 122.55 & 116.18 & - & - \\ Scene 03 & 125.59 & 119.45 & 127.28 & - \\ Scene 10 & 129.44 & 123.46 & - & 128.55 \\ Scene 11 & 123.63 & 117.30 & - & - \\ Scene 18 & 122.11 & 115.15 & - & - \\ Average & 124.66 & 118.31 & 127.28 & 128.55 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Achieved results in terms of PSNR, by embedding \(w_{2}\) (Dataset 2). Figure 2: Histogram of the average PSNR achieved for the watermark \(w_{1}\) and the watermark \(w_{2}\) (Dataset 1). ### Simulation Results Achieved by the LBMHI Algorithm

In this section, we focus on the simulation results achieved by the LBMHI algorithm, on Dataset 1 and on Dataset 2, which are comparable with the other state-of-the-art predictive-based approaches [11]. Moreover, it is important to note that the parameters of the LBMHI algorithm can be configured. Table 7 reports the simulations results, in terms of bits per pixel (BPP), achieved by the LMBHI compression algorithm, for each hyperspectral image of the Dataset 1 (rows from the second to the sixth), by considering the following configurations of the parameters: \(N\) = 8 and \(B\) = 1 (second column), \(N\) = 8 and \(B\) = 2 (third column), and \(N\) = 16 and \(B\) = 2 (fourth column). In Table 8, we report the experimental results achieved with Dataset 2 in the same manner of the ones reported in Table 7. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Hyperspectral Image**} & \multicolumn{3}{c}{**Average BPP**} \\ \cline{2-4}  & \(N\) = 8, \(B\) = 1 & \(N\) = 8, \(B\) = 2 & \(N\) = 16, \(B\) = 2 \\ \hline Cuprite & 5.0165 & 4.9886 & 4.8958 \\ Jasper Ridge & 5.0722 & 5.0271 & 4.9535 \\ Low Altitude & 5.3442 & 5.2995 & 5.2166 \\ Lunar Lake & 5.0207 & 4.9796 & 4.8850 \\ Moffett Field & 5.1012 & 5.0313 & 4.9594 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Achieved results in terms of BPP (Dataset 1).