IJPAM: Volume 110, No. 4 (2016)

Title

AN ALGORITHM OF BOUNDARIES DETECTION IN
LOW-CONTRAST RADAR IMAGES OF THE EARTH

Authors

Leonid Dorosinskiy$^1$, Tamara Lysenko$^2$
$^{1,2}$Ural Federal University
620002, Mir Street 19, Ekaterinburg, RUSSIAN FEDERATION

Abstract

One of the problems of radar images analysis of the Earth is the detection of boarders between areas with different normalized effective radar cross-sections. In this paper, we propose a computationally effective quasi-optimal algorithm capable for building approximation of such boarders with straight line segments for low-contrast radar images and arbitrary line for high-contrast radar images. To achieve computational efficiency we apply image segmentation and later approximation. Efficiency of the proposed algorithm was examined on a number of computer generated radar image fragments including low-contrast radar images. Proposed algorithm can be effectively implemented using modern parallel computation systems.

History

Received: August 27, 2016
Revised: October 4, 2016
Published: November 9, 2016

AMS Classification, Key Words

AMS Subject Classification: 60G35, 93E10, 94A12
Key Words and Phrases: radar imaging, image recognition, boarder detection, effective radar cross-section

Download Section

Download paper from here.
You will need Adobe Acrobat reader. For more information and free download of the reader, see the Adobe Acrobat website.

Bibliography

1
L.G. Dorosinsky, Radar signals class recognition algorithm synthesis, In: 24-th International Crimean Conference ``Microwave & Telecommunication Technology'' (CriMiCo'2014) Conference Proceedings, September 7-13, 2014, Sevastopol: Weber Publishing, 2 (2014), 1137-1138.

2
L.G. Dorosinsky. The research of the distributed objects' radar image recognition algorithms, In: 23-rd International Crimean Conference ``Microwave & Telecommunication Technology'' (CriMiCo'2013) Conference Proceedings, September 8-13, 2013, Sevastopol: Weber Publishing, 2 (2013), 1216-1217.

3
R.O. Duda, P.E. Hart. Pattern Classification and Scene Analysis, Wiley-Interscience, Oxford, 1973.

4
A.M. Chandra, S.K. Ghosh, Remote sensing and geographical information system, Narosa Pub. House, New Delhi, 2006.

How to Cite?

DOI: 10.12732/ijpam.v110i4.8 How to cite this paper?

Source:
International Journal of Pure and Applied Mathematics
ISSN printed version: 1311-8080
ISSN on-line version: 1314-3395
Year: 2016
Volume: 110
Issue: 4
Pages: 657 - 664


Google Scholar; DOI (International DOI Foundation); WorldCAT.

CC BY This work is licensed under the Creative Commons Attribution International License (CC BY).