The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008 
Table 3: Distance for JPEG 2000 at 1 bpppb. 
Degradation type 
Deg. param. 
Distance 
# of misclass. 
White noise 
50 
0.493597 
112 
White noise 
100 
0.492287 
163 
White noise 
200 
0.520257 
255 
White noise 
1000 
0.884674 
634 
Spectral smoothing 
3 
1.26847 
262 
Spectral smoothing 
5 
0.634936 
166 
Spectral smoothing 
7 
0.376314 
123 
Spatial smoothing 
13 
1.50541 
4248 
Spatial smoothing 
15 
1.22905 
3778 
Mixed smoothing 
11 
1.91304 
4881 
Gibbs 
50 
0.505195 
698 
Gibbs 
100 
0.510643 
425 
Table 5: Distance for JPEG 2000 at 0.5 bpppb on moffett4 image 
with degradation on moffett3. 
Table 4: Distance for a white noise of variance 100 on moffett4 
image with degradation on moffett3. 
Degradation type 
Deg. param. 
Distance 
# of misclass. 
White noise 
50 
0.107652 
112 
White noise 
100 
0.0435569 
163 
White noise 
200 
0.139344 
255 
White noise 
1000 
0.705412 
634 
Spectral smoothing 
3 
1.56918 
262 
Spectral smoothing 
5 
0.908723 
166 
Spectral smoothing 
7 
0.608943 
123 
Spatial smoothing 
13 
1.42293 
4248 
Spatial smoothing 
15 
1.12790 
3778 
Mixed smoothing 
11 
1.91772 
4881 
Gibbs 
50 
0.159746 
698 
Gibbs 
100 
0.198265 
425 
JPEG 2000 
0.5 
0.830507 
450 
JPEG 2000 
1.0 
0.449398 
142 
Degradation type 
Deg. param. 
Distance 
# of misclass. 
White noise 
50 
0.400136 
112 
White noise 
100 
0.419496 
163 
White noise 
200 
0.478324 
255 
White noise 
1000 
0.920144 
634 
Spectral smoothing 
3 
1.38425 
262 
Spectral smoothing 
5 
0.738476 
166 
Spectral smoothing 
7 
0.455491 
123 
Spatial smoothing 
13 
1.50678 
4248 
Spatial smoothing 
15 
1.22396 
3778 
Mixed smoothing 
11 
1.93958 
4881 
Gibbs 
50 
0.424221 
698 
Gibbs 
100 
0.407225 
425 
JPEG 2000 
0.5 
0.565506 
450 
JPEG 2000 
1.0 
0.129164 
142 
We also apply the method for a JPEG 2000 compression on mof- 
fett4 at a bitrate of 0.5 bpppb. Distances are presented on ta 
ble 5. The distance successfully identifies the degradation as be 
ing JPEG 2000. The mojfett4 image is more uniform, thus easier 
to compress. This property explains that degradations on mof- 
fett4 for a bitrate of 0.5 bpppb are similar to those on mojfett3 
at 1.0 bpppb. The number of misclassified pixels estimated by 
this method is 142, the real value being 82. There is a lack of 
reliability in this situation. 
In the situation where the method is applied to a different image, 
it is difficult to evaluate precisely the impact of the degradation 
on the application. However, this method successfully identifies 
the nature of the degradation caused to the image. It would be 
worthwhile to detail these results on a greater number of images 
and applications. 
Interest compared to traditional SNR 
SNR, as well as MSE or PSNR, which are derived measures, do 
not reveal the nature of the degradation and do not allow inferring 
the impact on applications. This fact is illustrated on figure 9. Di 
agrams are plotted for different degradations leading to the same 
SNR. The five degradations are applied to the moffett3 image to 
provide a SNR equal to 30 dB. We can clearly see from the dia 
gram that even if these degradations led to the same SNR, their 
characteristics are completely different. 
For the same image using only the SNR to measure the quality 
(here for a SNR of 30 dB), we cannot make the difference be 
tween 
a white noise with a variance of 2000: 1054 misclassified 
pixels; 
a spectral smoothing with an attenuation parameter of 4: 207 
misclassified pixels;