A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data

Perciano, T.; Tupin, F.; Hirata Jr., R.; Cesar Jr., R. M.

doi:10.1080/01431161.2016.1201227

Title: A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data

Journal Article · Wed Jul 13 00:00:00 EDT 2016 · International Journal of Remote Sensing

DOI:https://doi.org/10.1080/01431161.2016.1201227· OSTI ID:1764515

Perciano, T. ^[1]; Tupin, F. ^[2]; Hirata Jr., R. ^[3]; Cesar Jr., R. M. ^[3]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Telecom ParisTech, Paris (France)
Univ. of Sao Paulo (Brazil). Inst. of Mathematics

This article introduces a method for road network extraction from satellite images. The proposed approach covers a new fusion method (using data from multiple sources) and a new Markov random field (MRF) defined on connected components along with a multilevel application (two-level MRF). Our method allows the detection of roads with different characteristics and decreases by around 30% the size of the used graph model. Results for synthetic aperture radar (SAR) images and optical images obtained using the TerraSAR-X and Quickbird sensors, respectively, are presented demonstrating the improvement brought by the proposed approach. In a second part, an analysis of different types of data fusion combining optical/radar images, radar/radar images, and multitemporal SAR (TerraSAR-X and COSMO-SkyMed) images is described. Overall, the qualitative and quantitative results show that the fusion approach improves considerably the results of the road network extraction.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR); FAPESP

Grant/Contract Number:: AC02-05CH11231; 2011/50761-2

OSTI ID:: 1764515

Journal Information:: International Journal of Remote Sensing, Vol. 37, Issue 16; ISSN 0143-1161

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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Title: A two-level Markov random field for road network extraction and its application with optical, SAR, and multitemporal data

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