International Archives of Photogrammetry and Remote Sensing, Vol. 32, Part 7-4-3 W6, Valladolid, Spain, 3-4 June, 1999 
the input images to link related parameters of the observed 
Earth surface. 
c 
Fig. 1. Overall data fusion process in remote sensing. 
After having corrected system-induced and geometric errors in 
the dataset as indicated in Fig. 1, the images are fused to 
produce the higher spatial resolution using one of the following 
techniques: 
- RGB colour composites; 
Intensity Hue Saturation (IHS) transformation; 
Arithmetic combinations (e.g. Brovey transform); 
Principal Component Analysis; 
Wavelets (e.g. ARSIS method); 
- Regression Variable Substitution; 
- Combinations of techniques. 
The following sections describe the context and process of 
various techniques in more detail. 
3.1. Red-Green-Blue Colour Composites 
The so-called additive primary colours allow the assignment of 
three different types of information (e.g. image channels) to the 
three primary RGB colours. Together they form a colour 
composite that can be displayed on conventional media, e.g. 
cathode ray tube (CRT), with the parallel use of a LookUp- 
Table (LUT). The colour composite facilitates the interpretation 
of multi-channel image data due to the variations in colours 
based on the values in the single channels. Operations on the 
LUT and the histogram of the image data can enhance the 
colour composite for visual interpretation. 
The possibilities of varying the composite are manifold. 
Depending on the selection of the input image channels, the 
fused data will show different features. Very important for the 
colour composite is the distribution of the available 0-255 grey 
values to the range of the data. It might be of advantage to 
invert input channels before combining them in the RGB 
display with other data depending on the objects of interest to 
be highlighted (Wang et al., 1995). 
the colour aspects in its average brightness representing the 
surface intensity, its dominant wavelength (hue) and its purity 
(saturation) (Gillespie et al., 1986; Carper et al., 1990). The 
IHS values, commonly expressed in cylindrical or spherical 
coordinates, can be mapped to Cartesian coordinates through 
values v lt v 2 using a linear transformation (Harrison and Jupp, 
1990): 
f 1 
i 
l i 
fI 
Vi 
Vs 
Vi 
1 
1 
2 
V 1 
T* 
Te 
G 
V2> 
i 
l 
[Tl 
~Ti 
0 
H = 
tan~'(—) 
(b) 
S = V v 
2 
+V, 2 
V ! 
f 1 
1 
1 
N 
(R\ 
Vi 
Tb 
S 
fl 
G 
1 
1 
1 
* 
v 
V3 
V6 
1 
2 
Te 
0 
J 
(1) 
(2) 
In order to apply this technique for the enhancement of spatial 
resolution, a panchromatic higher resolution channel replaces 
the intensity component of a lower resolution multispectral 
dataset. 
There are two ways of applying the IHS technique in image 
fusion: direct and substitutional. The first refers to the 
transformation of three image channels assigned to I, H and S. 
The second transforms three channels of the dataset 
representing RGB into the IHS colour space which separates 
the colour aspects from its average brightness (intensity). Then, 
one of the components (usually intensity) is replaced by a 
fourth higher spatial resolution image channel, which is to be 
integrated. In many published studies the channel that replaces 
one of the IHS components is contrast stretched to match the 
latter. A reverse transformation from IHS to RGB as presented 
in Eq. 2 (Harrison and Jupp, 1990) converts the data into its 
original image space to obtain the fused image. 
3.3. Arithmetic Combinations 
The possibilities of combining the data using multiplication, 
ratios, summation or subtraction are manifold. The choice of 
weighing and scaling factors may improve the resulting images. 
Eq. 3 gives an example of a summation, and Eq. 4 of a 
multiplication technique used to combine Landsat TM with 
SPOT PAN as resolution merge (Yesou et al., 1993). 
DN f = A(w, * DN a + w 2 * DN b ) + B (3) 
DN f = A* DN a * DN b + B (4) 
3.2. Intensity-Hue-Saturation Colour Transform 
The IHS transformation (Eq. la-c) separates spatial (I) and 
spectral (H, S) information from a standard RGB image. It 
relates to the human colour perception parameters. It separates 
A and B are scaling and additive factors respectively and Wi and 
w 2 weighting parameters. DN f , DN a and DN b refer to digital 
numbers of the final fused image and the input images a and b, 
respectively.