Page 56 - Classification Parameter Estimation & State Estimation An Engg Approach Using MATLAB

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Parameter Estimation

Parameter estimation is the process of attributing a parametric descrip-
tion to an object, a physical process or an event based on measurements
that are obtained from that object (or process, or event). The measure-
ments are made available by a sensory system. Figure 3.1 gives an over-
view. Parameter estimation and pattern classification are similar
processes because they both aim to describe an object using measure-
ments. However, in parameter estimation the description is in terms of a
real-valued scalar or vector, whereas in classification the description is in
terms of just one class selected from a finite number of classes.

Example 3.1 Estimation of the backscattering coefficient from
SAR images
In earth observation based on airborne SAR (synthetic aperture radar)
imaging, the physical parameter of interest is the backscattering coef-
ficient. This parameter provides information about the condition of
the surface of the earth, e.g. soil type, moisture content, crop type,
growth of the crop.
The mean backscattered energy of a radar signal in a direction is
proportional to this backscattering coefficient. In order to reduce
so-called speckle noise the given direction is probed a number of
times. The results are averaged to yield the final measurement. Figure 3.2
shows a large number of realizations of the true backscattering

Classification, Parameter Estimation and State Estimation: An Engineering Approach using MATLAB
F. van der Heijden, R.P.W. Duin, D. de Ridder and D.M.J. Tax
Ó 2004 John Wiley & Sons, Ltd ISBN: 0-470-09013-8