723 
the image A. In the reflected signal in 
tensity formation it was supposed that 
the propagation and reflection conditi 
ons in every pixel are identical. Pig.3 
gives the image F, All images are quan 
tized by 16 levels. The dynamic range of 
images includes 256 levels. The backgro 
und frequency was set at f/ =100. In 
this case objects frequencies values are 
equal to =113, f«=1l6, f, =119, f* =122. 
A in exponential distribution is set 
equal to 100. In (1) /À7/T=40. Pig.4 
shows the image after the threshold pro 
cessing. This image is an initial seg 
mentation for the subsequent algorithm 
implementation. Pig.5 presents the re 
sultant image, obtained after 5 iterati 
ons of algorithm implementation, with 
5x5 pixels window size. Objects are sa 
tisfactory discriminated from the back 
ground. Individual points on the image 
edges are retained owing to the edge 
effect. 
Pig.5-10 show similar images for the 
case of objects arbitrary motion. Ob 
jects Doppler frequencies are chosen so 
that a part of pixels of their patterns 
have a frequencu which coincides with 
a background frequency and that is the 
most complicated case for the segmenta 
tion. The initial segmentation (fig.9) 
is implemented through two-threshold 
processing of image P (fig.8). The re 
sultant image (fig.10) is obtained in 
10 iterations of the algorithm imple 
mentation with 5x5 pixels window size. 
All objects are satisfactory extracted. 
Their shape is retained. The small-size 
regions which appeared due to false al 
arms may be easily removed at the sub 
sequent stages of image processing. 
On the whole the mathematical modeling 
confirms the effectiveness of proposed 
algorithms. The choice of variable pa 
rameters can be made only in the process 
of specific applied problems solving. 
The proposed algoritlims provide the ma 
thematically validated means of DOI seg 
mentation problem solution. The impor 
tance of the obtained results for prac 
tical application is obvious as far as 
two-dimensional convolution operations 
are easily implemented on specialized 
processors and the P image threshold 
processing used as the initial segmenta 
tion can be implemented with, the rate of 
information receipt. Taking into account 
the low rate of information receipt the 
binary segmentation algorithm implemen 
tation doesn’t require the VHSIC tech 
nology application. 
4. Dansac,J.,Meyzonnette,J.L.,1985.non 
laser Doppler rengefinding with hetero- 
dine detection and chirp pulse compres 
sion. Proceedings of Ihe SPIE,v.590: 
380-388. 
5. Derin, H., Cole,VV.S., 1986.Segmentation 
of textured images using Gibbs randomfi- 
elds.Computer vision, graphics and image 
processing,v.35:72-98. 
6. Prey,R,W.,1983. laser imaging radar 
sensor,Proceedings of the SPIE,V,415: 
2-12. 
7. Goodman,J.W., 1985.Statistical Optics. 
Wiley,New York. 
8. Hanson,P.R.,Elliott,H.,1982.Image se 
gmentation using simple Markov fields 
models.Сотри ter vision, graphics and im 
age processing,V.20:101-132. 
9. Harney,R.C.,Hull,R.J.,1980.Compact 
infrared radar technology.Proceedings of 
the SPltí,V,227:162-171. 
10. Harney,R.C.,1981.Military applicati 
ons of coherent infrared radar.Proceed 
ings of the SPIE,v.300:19£32. 
11. Hull,R.J.,1982.A place for laser in 
radar.Photonics spectra,v.16(4):60-65. 
12. Лешн Б.Р. ,1974.Теоретические основы 
статиотическои радиотехники.Том.I.С о- 
зетокое радио»Москва. 
13. Letalick,D.,1986.Measured signal am 
plitude distributions for a coherent FM- 
CW C0 9 laser radar.Applied optics,v.25 
(21) 0927-3938. 
14. Papurt,D,Shapiro, J. , 1981 .Atmospheric 
propagation effects on coherent laser 
radars.Proceeding of the SPIE,v.300:86 
-99. 
15. Pratt,W.K.,1978.Digital Image Proces 
sing. Wiley, New York, 
16.Sullivan,D.R.,1980.Active 10.6 m im 
age processing.Proceeding of the SPIE, 
v. 238:103-118. 
17. Therrien,C.W.,Quatieri,T,P.»Dudjion, 
T.E,,1986.Statistical model-based algo 
rithm for image analysis.Proceeding of 
the IEEE,v.74(4):532-551. 
18. Therrien,C.W.,1983.An estimation- 
theoretic approach to terrian image 
segmentation.Computer vision, graphics 
and image processing,v.22:313-326. 
19. Wang,J.Y.,1984.Image C0 9 laser radar 
field test.Applied optics,v.23(15):2565 
-2571. 
9. REFERENCES 
1. Albert,A.,1972.Regression and the 
Moore-Penroce Pseudoinverse.Academic 
Press,New York. 
2. Besag,J.,1974.Special interactions 
and statistical analysis of Lattice sys 
tems. Journal of the Royal Statistical 
Society,ser.B,v.36:192-236. 
3. БорисенкоИ.B 0 »Златопольскик А.А.»Муч 
ник А.Б.,1987.Сегментация изображения. 
Автоматика и телемеханика,74 (4):4-25