ITERATIVE ALGORITHM FOR MULTIDIMENSIONAL IMAGE ANALYSIS
V.M.Lisitsyn, V.A.Stephanov, N.N.Pasechny, K.V.Obrosov
The Research Institute of Aviation Systems, Moscow, Russia, ISPRS Comission III
ABSTRACT
The paper considers
multidimensional speckled images;
the presence of some statistical dependence between the value of one
assessment
provides a common approach to segmentation procedure
of image generation
and the validity of value
processes feature
the method of se
he
entation and analysis of one class of
specific feature of these images is
component
of the
other. The proposed method
irrespective of physical
under stated conditions. For normal
. v. by . . .
parameter assessment distribution based on a maximum a posteriori probability
criterion.
Each region being segmented is
assigned an index. At the same time
algorithm allows to carry out analysis of the reference scene, since its output
is not only a se
KEY WORDS: Algorithm, Image Analysis, Image Processing, Remote
INTRODUCTION
In the automatic analysis of scenes, the
main problem is the conversion of
information, the image of a scene
represented as a two-dimensional
function, into some description of this
image. This description can be stored in
a memory section which is thousands times
smaller than that required for storing
the image. At the same time, the
information contained in the original
image and essential for the above
analysis is retained and converted into a
processable form (Duda,1973).
An indispensable stage of image
processing aimed at preparing iis
desoription is segmentation which
consists in fragmenting the image into
regions which are ooherent by some
atiribute. Segmentation can be aimed at
discerni scene objects and suppres-
si insignificant details (Bopmeenxo,
1987).
We shall have a look at
image types - a class
images which feature some statistical
correlation between the observed value of
one component and the degree of certainty
one of numerous
of 4-dimensional
of the estimated value of another compo-
nent. This correlation is characteristic
of multidimensional speckle images
generated by remote sensing facilities,
such as radars, radio-optical ranging and
deteotion systems and laser radars. In
the course of the generation of these
images, each pixel (7,ÿ) is assigned a
a
detector-outputted signal/noise ratio and
some parameter of the reflected signal is
estimated. The fourth, estimated
component of the image oan be represented
by such parameters as the velocity,
range, radiation polarization factor,
ete, or their combination, for which the
degree of estimate certainty is
probabilistically related to the
signal/noise ratio.
obtained by means o
| feature a specific e
884
ented image but also characteristics of each of regions being
extracted (location and parameter vector).
Sensing Application
which is received is a
superposition of functions of scattering
by a set of elementary =—reflecti
surfaces, characterized by differen
phases and amplitudes. Interference
results in that in each pixel the
intensity of the reflected signal takes
random, Weibull-distributed value, which
generates the so-called speckle
structure. The speckle structure of the
image has a considerable effect on the
accuracy of estimates of the component
being evaluated, which, in the first
approximation, is specified by the ratio
(Dansac,1985):
reflected signal
an — 1m, (1)
[A7 A,
where A is the intensity of the
received, A is
noises. Therefore values
elements of the speckle image
being estimated can have
different estimate variances
from occasional fluctuations.
signal
the power of internal
of different
component
essentially
resulting
(Lisitsyn,
proposes an
For the above class of images,
1990; JmcmuwH, 1990)
iterative algorithm for segmenting
Doppler laser radar images. This
algorithm formed a binary image whose
pixels belonging to patterns which
represented moving objeots had a value of
"|" and the remaining pixels had a value
of "O". Drawbaoks of the algorithm are
instable operation when patterns
representing different objects touched
each other or scene objects partially
shade each other. Moreover, that the
segmented image is binary makes it
difficult to resolve discerned patterns.
The algorithm which will be proposed
below oan be considered as a
generalization of the algorithm for
binary segmentation of Doppler laser
radar images, to the oase of nonbinary
segmentation and its extension to other
types of images belonging to the same