International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 
112 
Image 
Original 
AIF 
IHS 
bands 
image 
LISS-2 
P 
89.6 
89.6 
91.1 
green 
G 
21.7 
21.0 
26.0 
LISS-3 
P 
32.1 
32.0 
33.0 
red 
G 
13.0 
12.6 
14.8 
LISS-4 
P 
100.6 
100.8 
99.4 
NIR 
G 
26.1 
23.6 
20.1 
Table 1. Statistics of differences between original and 
degraded image bands (IRS-1C). 
Comparison of the correlation coefficients leads to similar 
results (see Table 2). It can be clearly seen that the AIF image 
bands correlate highly with the original data, whereas the 
correlation between the IHS merged image and the original 
image is significantly lower. As expected, the difference in the 
near infrared band is highest as it is least correlated with the 
panchromatic image. 
Bands 
AIF 
IHS 
LISS-2 
0.99 
0.92 
LISS-3 
0.99 
0.97 
LISS-4 
0.97 
0.85 
Table 2. Correlation coefficients between AIF and IHS 
merged images with the original ones (1RS-1C). 
3.2. Urban case study 
In order to evaluate the AIF on very high resolution data, a 
second study was performed on airborne scanner data. The 
image was acquired by a Daedalus AADS 1268 ATM (Airborne 
Thematic Mapper) scanner in August 1991 and covers an area in 
the south of Vienna, Austria. The spectral resolution of this 
scanner comprises 11 bands. For the case study only the 6 bands 
that correspond to the spectral bands of Landsat TM were used. 
The scanner data were geocoded to the Austrian reference 
system (Gauß-Krüger M34) with a spatial resolution of 6m. 
The focus of this study was an analysis of AIF results compared 
to multispectral images observed with the high resolution of the 
panchromatic image. In order to perform this comparison the 
ATM image (denoted by org in Table 4) was degraded to a 
resolution of 18m (denoted by deg in Table 4) and an artificial 
panchromatic image was computed by averaging bands 1 to 4 on 
the 6m pixel basis. Next, an AIF was performed on the degraded 
image bands and the panchromatic image resulting in an 
artificial image stack with a resolution of 6m. This image stack 
was then compared to the original image data. 
As it can be seen in Table 3, the global mean values of all three 
images (original, degraded and fused) are stable, thus no spectral 
distortion occurred during the fusion process. Again the standard 
deviation of the degraded and the fused image is lower than the 
one of the original image. For more detailed analysis the 
correlation between the three image stacks were computed (see 
Table 4). Whereas the correlation between the original image 
and the degraded image lies between 0.82 and 0.85, the 
correlation between the original and the AIF is significantly 
higher except for band 5. This effect might be due to the fact 
that the correlation between the multispectral and the pan 
chromatic image is lowest for band 5. 
Image 
Original 
Degraded 
AIF 
bands 
image 
image 
image 
ATM 1 
P 
85.3 
85.4 
85.1 
blue 
G 
27.3 
19.5 
19.9 
ATM 2 
P 
56.3 
56.3 
56.2 
green 
G 
19.5 
14.1 
14.5 
ATM 3 
P 
51.2 
51.2 
51.0 
red 
G 
24.2 
18.0 
18.5 
ATM 4 
P 
67.5 
67.6 
67.7 
NIR 
G 
21.7 
15.7 
16.0 
ATM 5 
P 
69.2 
69.1 
69.3 
NIR 
G 
27.3 
21.0 
20.0 
ATM 6 
P 
71.6 
71.5 
71.4 
MIR 
G 
31.7 
23.7 
23.6 
Table 3. Statistics of differences between original and 
degraded image bands (ATM). 
Bands 
org - deg 
org - AIF 
deg - AIF 
ATM 1 
0.82 
0.94 
0.87 
ATM 2 
0.83 
0.94 
0.88 
ATM 3 
0.84 
0.94 
0.89 
ATM 4 
0.82 
0.93 
0.82 
ATM 5 
0.85 
0.84 
0.87 
ATM 6 
0.84 
0.89 
0.88 
Table 4. Correlation coefficients (ATM). 
A visual comparison shows the benefits and limitations of the 
AIF (Fig. 4). Compared to the degraded image, the fused image 
is clearly sharper and shows no blockiness. Although most of 
the object structures seen in the original image will be found in 
the fused image as well, some of the smaller objects are blurred 
(e.g. garden area in the upper left part of the image, single 
buildings in the village in the lower part). In these cases the 
single objects are too small to be reconstructed from the 
degraded image. 
3.3. Forest case study 
In a third case study the use of AIF was tested for a forest 
application. The objective was the derivation of a forest mask 
from Landsat TM imagery in combination with a panchromatic 
SPOT image in an alpine region. The two images were acquired 
on August 18, 1992 and August 17, 1992 respectively. The area 
is located in the center of Austria, in the Dachstein region, 
Styria (centered on 13°40’E / 47°20’N). Both images were