# Satellite Image Compression Guided by Regions of Interest
## 3 Results
Cloud shadows can generate differences between the image and the reference image that exceed the threshold value \(\tau_{3}\), as pointed out by the white dots in the tiles A8, B8, and C8, of Figure 11b. In general, detection failures caused by cloud shadows, or by the undetected clouds, will reduce the system's performance on dry land. In water regions, false alarms caused by cloud shadows were not observed. However, false alarms on the vessel detection step can be seen due to small portions of clouds, which is the case for tiles F7, G7, I5, G4, G3, I3, E1, and H1. Tiles E2, H8, J10, and E13, can be considered tiles containing well-defined small vessels. In fact, false alarms caused by undetected clouds can reduce the efficiency of the proposed method in terms of information saved, but they cannot compromise the useful information. To illustrate that issue, Figure 12a shows the NIR band of the image 9 compressed with the proposed method, and Figure 12b shows its lower-left quadrant zoomed in. The tiles A4, C4, D2, D1, and C1, were lossless compressed, but the other tiles in Figure 12b were lossy compressed. Thus, uninteresting content (e.g., tile A1) had loss of details, and content with uncertainty had its details preserved (e.g., tile A4). According to Table 2, the PSNR value and the final coding rate reached for image 9 were, respectively, 63.3 dB and 2 bpp. The gains achieved by using the proposed method were 0.320 and 0.294 for \(\beta=0.2\) and \(\beta=0\), respectively. Figure 13 shows the results of the proposed method applied to the image 10, which is another cloudy image. Similarly to the results of image 9, cloud shadows on the ground can be seen to increase the number of tiles marked as \"changed\" in the dry-land region. At all, the tiles classified as \"No-changes\" were the tiles B13, C13, D13, D12, and E12. Other tiles that were lossily compressed and showed dry land were due to the presence of clouds itself (cloudy tiles), such as tiles A1, A2, and C4, for instance. In the water region, two tiles were wrongly marked as containing vessels. Tile F12 resulted in a false alarm due to noise in image synthesis, and tile G2 resulted in a false alarm due to the presence of clouds. The other tiles in the water region were not classified as ROI, and were compressed with the coding rate \(\beta\). The gains for image 10 were 0.307 for \(\beta=0.2\) and 0.283 for \(\beta=0\). Figure 12: NIR band of the image 9 compressed with the proposed method: (**a**) compressed image; (**b**) compressed image zoomed in. The cloud cover in image 11 is similar to that in image 10, producing somewhat similar gains, as described in Table 2. In image 12, the cloud portion is slightly smaller than the cloud portion in image 10, as shown by Figure 13(a). Thus, the negative impacts of cloud shadows on the change detection step are smaller, being limited to tiles A4, A5, and A6, as illustrated by the detections in Figure 13(b). In the water region, four tiles were correctly marked as containing vessels. In particular, it is interesting to observe tile J2 in Figure 13(c), which contains two possible vessels almost covered by clouds (near the border with tile K2). Tile J2 is an example of a tile partially covered by clouds, but with interesting content elsewhere. This justifies using high values of \(\tau_{2}\) to avoid missing out on interesting content. The results of images 13 to 16 are similar to those already discussed for the group of images containing clouds. Moving forward with the description of the results, the behavior of the system in fog scenarios can be discussed through the results of images 18 and 20. Figure 14(a) illustrates a case of moderate fog, whereas Figure 15(a) is a scenario of denser fog along with small clouds. Figure 7:0 Results for image 12: (**a**) RGB image (truncated at 2000); (**b**) binary image; (**c**) labeled tiles (truncated at 4000). Figure 7:1 Results for image 10: (**a**) RGB image (truncated at 2000); (**b**) binary image; (**c**) labeled tiles (truncated at 4000).