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Husoy, 1999; Reed & Hans Du Buf, 1993). For most of these methods, a single texture
parameter is applied to the discrimination of classes. In this chapter, which applies to
images from a radar sensor, we introduce the notions of vector texture, patterns and valleys
of the histogram and textural signature for the characterization of classes of land, and show
that textural parameters of order higher than 2 are more effective for discrimination of these
classes.
In the following, we will present the arborescent method of textural parameters evaluation,
followed by the presentation of notion of mode and valley of histogram in SAR image
analysis. The criteria of choosing textures parameters are also presented. Once the
characterization of the various training zones is done and the classification algorithm is
presented. Finally, we present some experimental results.
2. Problem context
The usefulness of image classification is not to be demonstrated today. A good classification
requires a better identification of information classes on the image. This identification
requires the selection of good feature parameters.
3. Methodology
Our methodology is divided into two parts: the first part concerns the improvement of the
computational time required for the evaluation of textural parameters. The second part
deals with an approach of SAR images classification.
3.1. Formulation of high order of statistical textural parameters
Basically, statistical textural parameters are function of the occurrence frequency matrix
(OFM), which is used to define the occurrence frequency of n-ordered gray levels in the
image.
3.1.1. The occurrence frequency matrix (OFM)
In an image with
Ng+1
levels of quantification, the OFM of order
n >1
is a
(Ng+1)
n
size matrix.
In this matrix, each element
⋯
expresses the occurrence frequency of the
n-
ordered
pixels
(i
0
,i
1
, …,i
n-1
)
following the connection rule
R
n
(d
1
,d
2
,…d
n-1
,θ
1
,θ
2
,…θ
n-1
)
. This connection
rule defines the spatial constraint that must be verified by the various pixels of the
n-
ordered
pixels
(i
0
,i
1
,…,i
n-1
)
used in the occurrence frequency matrix evaluation. This rule means that
the pixel
i
k+1
(0<k<n)
is separated to the pixel
i
k
by
d
k-1
pixels in the
θ
k
direction. For the sake of
simplicity,
R
n
(d
1
,d
2
,…d
n-1
,θ
1
,θ
2
,…θ
n-1
)
will be noted by
R
n
in the following.
3.1.2. The textural parameters
A parameter of texture
in any order
is a real function defined in general manner by
the equation given after: