269.

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P_rmin and P_rmax each denote minimal power and maximal power occurring within a polarisation signature, respectively. Since CoV relates to the surface roughness, it can be used as a discriminating feature in classification. As the value of CoV increases, the measured surface tends to be rougher. The concept of CoV is based on the following observations (Evans et al., 1988). The polarisation signature for each resolution element represents the sum of the polarisation signatures of many individual measurements. If the surface being measured is smooth, the scattering mechanisms from a group of scatterers should be identical. Therefore, the maxima (minima) of a scattering mechanism should coincide with the maxima (minima) of the other scattering mechanisms. When the composite polarisation signature is derived, it will produce a composite signature in which there is a large difference in magnitude between maximal and minimal backscatter, and, thus, the polarisation signature will result in more peak- and valley-like shapes. As a result, the value of the CoV will be small (i.e. closer to 0). Conversely, if the measured ground surface is rough, several different scattering mechanisms may result, the backscatter maxima and minima may occur together from different individual scatterers, and a relatively flat polarisation signature shape will be produced (equivalently, CoV will be large, i.e. close to 1).

1.8 Radar speckle suppression

Due to random fluctuations in the signal observed from an spatially extensive target represented by a pixel (or image resolution element), speckle noise is generally present on a radar image. Speckle has the characteristics of a random multiplicative noise (defined below) in the sense that as the average grey level of a local area increases, the noise level increases. In a SAR imaging system, speckle effects are more serious (Goodman, 1976). SAR can achieve high resolution in the azimuth direction independent of range, but the presence of speckle decreases the interpretability of the SAR imagery. If such imagery is to be used in classification, then some form of pre-processing to reduce or suppress speckle is necessary.

There are two approaches to the suppression of radar image speckle. The first method is multi-look processing, while the second method uses filtering techniques to smooth the speckle noise.

1.8.1 Multi-look processing

Radar speckle can be suppressed by averaging several looks (images) to reduce the noise variance. This procedure is called multi-look processing. As the radar sensor moves past the target pixel, it obtains multiple looks (i.e. returned samples). If these looks are spaced sufficiently far apart they can be considered to represent individual observations. The relationship

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