275.

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Page 46

(1.42)

where z′ is the optimal linear approximation of z. The minimising mean square error estimate of the noise-free signal is obtained as (Lee, 1986):

(1.43)

Here, k is a weighting coefficient, and is defined as (Lee, 1986)

(1.44)

Taking Equations (1.41), (1.43) and (1.44) together, it can be shown that the estimated value of the noise-free signal x is a function of z, μz, μv, σz2, and σv2. Figure 1.28 shows the procedure for applying the Lee filter to perform speckle suppression.

The effectiveness of Lee filter can be more clearly seen in terms of an alternative expression of the filter model (Baraldi and Parmiggiani, 1995b). First, the form of Equation (1.41) can be converted in accordance with Cx. Equation (1.41) then becomes:

(1.45)

Equation (1.45) shows that in a flat area which is equival-

Figure 1.28 Speckle filtering using the Lee filter.

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Classification Methods for Remotely Sensed Data
Classification Methods for Remotely Sensed Data, Second Edition
ISBN: 1420090720
EAN: 2147483647
Year: 2001
Pages: 354

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