which assist in the interpretation process. 'The cloud classification process is sup 
ported by radio sonde reference data (RSA). 
The following assumptions have been made for the cloud classification process: 
* clouds are black body emitters 
e the instantaneous field of view of the radiometer is completely covered 
by clouds (no mixed pixel effects'). 
Classification of scene segments is implemented after division of the image frame 
into sub-segments for which the RSA-values (approx. 35) can be assumed repre 
sentative. For this process the minimum distance on earth surface (not in the 
image matrix) is calculated. The cloud upper limit is assumed to be at a height 
where radiation temperatur and the surrounding temperature coincide. This is. 
however, only valid for a completely transparent atmosphere. Under real condi 
tions an atmospheric correction would have to be performed. This paper uses a 
one- channel parametric correction scheme. In so doing the radiation and tem 
perature deficit above the clouds (between cloud top and the satellite) as a result 
of the rest band water vapour absorption in the large atmospheric window (IR- 
channel) is simulated. This is done by integration of the Schwarzschild-Emden 
differential radiation transfer equation for stationary, horizontally homogeneous 
conditions and neglection of IR scattering. 
The spectral transmission function of wafer vapour is obtained in parametric form 
using effective spectral mass absorption coefficient from literature. The reduced 
water vapour mass above the clouds is obtained with the help of radio sonde 
measurements (humidity, temperature). This procedure reduces the temperature 
of the main pressure levels by an. amount induced through atmospheric influence 
under the condition of a black body emitter. The in this manner corrected elima 
to logical and regional temperature tables are used to perform a threshold classifi 
cation of the METEOS AT infrared image segments. 
3. image compression techniques 
3.1. A parallel two-dimensional procedure for micro-adaptive image 
coding 
Following the classification process a further reduction of the data volume can be 
performed by redundancy reduction. The relevant algorithms can also be applied 
to achieve compression of non-classified meteorological images such as NOAA 
scenes. To achieve that goal a two-dimensional adaptive compression procedure 
is applied. The images are decomposed using a quadtree structure. Image coding 
is performed by explicit transmission of resolution and gray level, while the loca 
tion of the pixels is implicitly given by the algorithm. Resolution is determined by 
the local contrast of images. 
Higher compression rates can be achieved by tolerating differences between the 
original and the decoded image. The resolution is controlled in such a way that 
small details are transmit ted if the local contrast, is high. This procedure avoids to 
a great extend blurring of edges. 
This procedure has been implemented as a parallel as well a sequential algorithm.