PSEUDOCOLOR PHOTOMAPS PRODUCTION USING NEURAL NETWORKS 
Karel Charvát, Vladimir Cervenka 
Geodetic and Cartographic Enterprise, Prague 
Remote Sensing Centre 
Introduction 
Gathering of information on the land use belongs to the main 
goals of remote sensing methods. This task is of special 
importance in regions with complicated structural zoning, e.g. 
in urban aglomerations and their surrounding. At present, 
Thematic Mapper (TM) data are frequently exploited for these 
purposes. Therefore, a great attention has been also paid to 
the development of their interpretation. Individual methods 
differ each other as for the complexity and the level of 
automation. There are a simple methods based on visual 
interpretation and also fully automated processes based on the 
principles of artificial intelligence. Selection of a suitable 
method can be made from different points of view. The most 
important of them will often be the costs of processing. Lower 
price is one of the main reasons for using the combinations of 
visual and computer methods. 
A simple method of production of 1 : 50 000 pseudocolor 
photomaps was described in [1]. The principle of this methods 
consisted in the production of a pseudocolor composite and its 
superimposition into the line map. The process described was 
divided into four steps: 
a) transformation of the primary TM data into three color 
components, 
b) histogram equalization of separate color components, 
c) refining of the pixel size, 
d) color composite production from three components and its 
superimposition into the map. 
There will be described a new improved technology in this 
paper. It applies modern principles of artificial 
intelligence, especially from the branche of neural networks. 
Transformation of the primary data into three color components 
Usual way of color composite production consist in the 
selection of three spectral bands, their conversion into the 
analogue form on the film material and common projection with 
red, green and blue filter by means of the multispectral 
projector. However, this way is not suitable for TM data, 
because only a part of the information, contained in six or 
seven TM bands, can be exploited. Therefore, it seems to be 
useful to transform all disponsible spectral bands into three 
"synthetic" ones. 
The use of the transformation called "Tasseled Cap" for this 
purpose has been described in [1]. The results obtained by 
this transformation was satisfactory but this method had also 
some disadvantages. At first, the data had different dynamics 
in the individual bands, and in some cases the part of 
information had been lost. 
A new transformation will be described here. It enables to 
comprimate effectively the whole information contained in 
original'TM data into three new synthetic channels, as well as 
its decomprimation back into the original channels. This 
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