INTERACTIVE ALGORITHM FOR SELECTION OF LINEAR OBJECTS ON AERIAL PHOTOGRAPHS AND SATELLITE IMAGES
Abstract
A new approach to the problem of extraction of linear objects on aerial photographs and satellite images is presented. An interactive algorithm of detection of linear objects by broken lines, based on the developed approach, is offered. The algorithm provides fast detection of linear objects,it is easy tuned and convenient for practical use. It is enough precise and reliable to process middle or low reso-lution aerial photographs and satellite images. Specificity of its parallel program implementation is also described. The developed parallel program implementation allowed to reduce the execution time of the algorithm by several orders. Estimates of execution time of versions of the algorithm, which are intended for video cards, are given in the article.
About the Authors
Э. Н. Seredin
Объединенный институт проблем информатики НАН Беларуси
Belarus
Belarus
B. A. Zalesky
Объединенный институт проблем информатики НАН Беларуси
Belarus
Belarus
References
1. LandsatLook Viewer [Электронный ресурс]. – Mode of access : http://landsatlook.usgs.gov. – Date of access : 28.09.2014.
2. Кочуб, Е.В. Анализ методов обработки материалов дистанционного зондирования Земли / Е.В. Кочуб, А.А. Топаз // Вестник ПГУ. Сер. F. – 2012. – № 16. – С. 132–140.
3. Supreet, S. Automatic Road Detection of Satellite Images – A Survey / S. Supreet, B. Seema // Intern. J. of Computer Applications & Information Technology. – 2013. – Vol. 3(2). – P. 32–34.
4. Kalaivanan, R. Survey on Road Extraction From High Resolution Satellite Images / R. Ka-laivanan, S. Mishmala // Intern. J. of Advanced Research in Computer and Communication Engineer-ing. – 2013. – Vol. 2(10). – P. 4156– 4159.
5. A Family of Quadratic Snakes for Road Extraction / M.N. Dailey [et al.] // Lecture Notes in Computer Science. – 2007. – Vol. 4843. – P. 85–94.
6. Dal Poz, A.P. Dynamic Programming Approach For Semi-Automated Road Extraction From Medium- And High-Resolution Images / A.P. Dal Poz, G.M. do Vale // ISPRS Archives. – Vol. 34 (3/W8). – P. 87–91.
7. Urban digital map updating from satellite high resolution images using GIS data as a priori knowledge / T. Bailloeul [et al.] // Remote Sensing and Data Fusion over Urban Areas, 2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban Areas. – Urban, 2003. – P. 283–287.
8. Niu, X. A semi-automatic framework for highway extraction and vehicle detection based on a geometric deformable model / X. Niu // Photogrammetric Engineering and Remote Sensing. – 2006. – Vol. 61. – P. 170–186.
9. Automatic Road Extraction from Satellite Imagery Using LEGION Networks / J. Yuan [et al.] // Proc. of Intern. Joint Conference on Neural Networks. – Atlanta, Georgia, USA, 2009. – P. 3471–3476.
10. Lacoste, C. Unsupervised line network extraction in remote sensing using a polyline process / C. Lacoste, X. Descombes, J. Zerubia // Pattern Recognition. – 2010. – Vol. 43 (4). – P. 1631–1641.
11. Color image segmentation: advances and prospects / H. Cheng [et al.] // Pattern Recogni-tion. – 2001. – № 34. – P. 2259–2281.
12. Sniedovich, M. Dynamic programming. Foundations and principles / M. Sniedovich. – Bo-ca Raton : CRC Press Taylor & Francis Group, 2011.
13. Handbook of Learning and Approximate Dynamic Programming / J. Si [et al.] // Wiley-IEEE Press, 2004.
14. Боресков, А.В. Основы работы с технологией CUDA / А.В. Боресков, А.А. Харламов. – М. : ДМК Пресс, 2010. – 232 с.
15. Сандерс, Дж. Технология CUDA в примерах: введение в программирование графиче-ских процессоров / Дж. Сандерс, Э. Кэндрот. – М. : ДМК Пресс, 2011. – 232 с.
16. Zalesky, B.A. Interactive extraction of roads and rivers in low resolution or noisy satellite images / B.A. Zalesky, E.N. Seredin // Proc. of 12th Intern. Conf. PRIP2014. – Minsk, 2014. – P. 329–334.
Review
For citations:
Seredin Э.Н., Zalesky B.A. INTERACTIVE ALGORITHM FOR SELECTION OF LINEAR OBJECTS ON AERIAL PHOTOGRAPHS AND SATELLITE IMAGES. Informatics. 2014;(4):66-74. (In Russ.)
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