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Computer Optics, 2016, Volume 40, Issue 5, Pages 721–728 (Mi co293)  

IMAGE PROCESSING, PATTERN RECOGNITION

The hybrid CPU/GPU implementation of the computational procedure for digital terrain models generation from satellite images

V. A. Fursovab, E. V. Goshinab, A. P. Kotovab

a Samara National Research University, Samara, Russia
b Image Processing Systems Institute îf RAS – Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

Abstract: In this paper a procedure of building a digital terrain model (DTM) from the satellite images is researched. The procedure is based on the authors' previously developed algorithms of fast image matching for building disparity maps implemented on GPUs (Graphics Processing Units). In this paper we propose a computational procedure for constructing a DTM from the satellite stereo images. Experimental studies have shown that while this procedure constructs a DTM that may be less accurate than the one achieved with the use of the ENVI software, it offers a significantly shorter time of processing.

Keywords: digital image processing, stereo images, 3D-scene reconstruction, image matching, CUDA-technology, ENVI.

Funding Agency Grant Number
Russian Science Foundation 14-31-00014
The work was funded by the Russian Science Foundation (grant #14-31-00014).


DOI: https://doi.org/10.18287/2412-6179-2016-40-5-721-728

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Full text: http://www.computeroptics.smr.ru/.../400515.html
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Received: 17.07.2016
Accepted:31.10.2016
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Citation: V. A. Fursov, E. V. Goshin, A. P. Kotov, “The hybrid CPU/GPU implementation of the computational procedure for digital terrain models generation from satellite images”, Computer Optics, 40:5 (2016), 721–728

Citation in format AMSBIB
\Bibitem{FurGosKot16}
\by V.~A.~Fursov, E.~V.~Goshin, A.~P.~Kotov
\paper The hybrid CPU/GPU implementation of the computational procedure for digital terrain models generation from satellite images
\jour Computer Optics
\yr 2016
\vol 40
\issue 5
\pages 721--728
\mathnet{http://mi.mathnet.ru/co293}
\crossref{https://doi.org/10.18287/2412-6179-2016-40-5-721-728}


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