# Satellite Image Compression Guided by Regions of Interest
## 3 Results
In this paper, the labeled tiles are marked as follows:* Tiles with ROI in dry-land regions are outlined with yellow traced lines;
* Tiles with possible vessels in water region are outlined with blue traced lines;
* Cloudy tiles are crossed with red traced lines. * Other tiles without interesting content are crossed with cyan traced lines; \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Image**} & **Bits per** & \begin{tabular}{c} **Mean** \\ **Squared** \\ **Error** \\ \end{tabular} & \begin{tabular}{c} **Peak** \\ **Signal-to-** \\ **Noise Ratio** \\ \end{tabular} & **Amount of** & **Gain for** & **Gain for** & \
\begin{tabular}{c} **Bits per** \\ **Pixel with** \\ **Pixel with** \\ \end{tabular} &
\begin{tabular}{c} **Bits per** \\ **Pixel with** \\ **CCSDS** \\ \end{tabular} \\ \hline  
\hline \hline \end{tabular}
\end{table} 
Table 2: Numerical results. Figure 7: Results of image 1: (**a**) binary image; (**b**) labeled tiles (truncated at 4000). Figure 7b shows the NIR band of image 1 compressed with the proposed method, in which the labeled tiles are marked. Tiles A10, A12, A13, B7, B11, B12, C11, and C12 were labeled as containing changes, whereas tiles E1, F1, F2, F3, F13, H4, I7, I11, K2, K13, L6, and M1 were labeled as containing vessels. The other remaining tiles were labeled as not containing interesting content. As pointed out by Table 2, the image distortion achieved for image 1 was 59.5 dB of PSNR. To simplify observing the image distortion's impacts, Figure 8a shows the NIR band compressed with the proposed method but without the tile markings, and Figure 8b shows its upper-left quadrant zoomed in. The differences in image distortion between the tiles compressed with \(r=\alpha\) and \(r=\beta\) can be seen, for instance, when comparing the tiles B13 and C13 (lossy compressed) with the tiles B12 and C12 (lossless compressed). It is important to mention that the images in this paper contain small amounts of distortion resulting from the editorial process, such as resizing or file manipulation. The final amount of information required to compress the NIR band of the image 1 is 1.09 bpp, which results in gains of 0.155 for \(\beta=0.2\), and 0.128 for \(\beta=0\). This means that only 15.5% of the information required for lossless compression of the whole image is needed. This percentage can be reduced to 12.8% in case of discarding the tiles without ROI. Image 2 results in smaller gains. It requires 26.3% and 23.6% of the information, respectively, for \(\beta=0.2\) and \(\beta=0\). The differences in the gains between image 1 and 2 are due to the numbers of tiles marked as ROI. Indeed, 38 tiles were marked as ROI for image 2, which is almost the double the number for image 1. As a consequence, the increase in the number of tiles that were losslessly compressed raised the final coding rate to 1.67 bpp. An increase in image quality was achieved also, resulting in a PSNR value of 60.3 dB. Figure 9a-c show the RGB image, the labeled tiles, and the compressed NIR band image, respectively. Figure 8: NIR band of the image 1 compressed with the proposed method (truncated at 4000): (**a**) compressed image; (**b**) compressed image zoomed in. As shown by Figure 9, image 2 has new changes in the upper-left quadrant of the image and many vessels in the water regions. The changes in dry-land region comprise 10 tiles, and possible vessels cover 28 tiles, as illustrated by Figure 9. According to Table 2, the same number of tiles marked as ROI in image 2 was marked in images 14 and 17, but resulting in different values of gains. As mentioned in Section 2, the coding rate \(\alpha\) is variable in order to ensure lossless compression. For the lossily compressed tiles, \(\beta\) was fixed to 0.2, which generated the differences in the PSNR values. Thus, the differences in gains for images 2, 14, and 17, were due to the lossless compression. The same was true for other images with the same number of ROI. The results for most other no-cloud images in Table 2 are similar.