A Markovian Approach for DEM Estimation From Multiple InSAR Data With Atmospheric Contributions
Accurate digital elevation model (DEM) estimation using synthetic aperture radar interferometry still remains a challenging problem in the geographical information science community, particularly in dealing with a high noise rate and atmospheric disturbances. Such task suffers from the lack of effic...
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| Veröffentlicht in: | IEEE geoscience and remote sensing letters 2012-07, Vol.9 (4), p.764-768 |
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| container_title | IEEE geoscience and remote sensing letters |
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| creator | Shabou, A. Tupin, F. |
| description | Accurate digital elevation model (DEM) estimation using synthetic aperture radar interferometry still remains a challenging problem in the geographical information science community, particularly in dealing with a high noise rate and atmospheric disturbances. Such task suffers from the lack of efficient and reliable methods to overcome these artifacts. This work provides a method that aims to solve this problem through a Bayesian formulation with the Markovian energy minimization framework. The DEM is generated from a set of multifrequency/multibaseline interferograms using a multichannel phase unwrapping algorithm combined with an estimation method of the atmospheric artifacts. A set of experimental results illustrates the effectiveness and robustness of the proposed approach. |
| doi_str_mv | 10.1109/LGRS.2011.2181326 |
| format | Article |
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(IEEE) Jul 2012</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c393t-d1d5825351959ca591d7258e1e7452639e27b3396721c5209e33f8b194f559323</citedby><cites>FETCH-LOGICAL-c393t-d1d5825351959ca591d7258e1e7452639e27b3396721c5209e33f8b194f559323</cites><orcidid>0000-0002-3110-8183</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6143980$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,314,777,781,793,882,27905,27906,54739</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6143980$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://telecom-paris.hal.science/hal-02286358$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Shabou, A.</creatorcontrib><creatorcontrib>Tupin, F.</creatorcontrib><title>A Markovian Approach for DEM Estimation From Multiple InSAR Data With Atmospheric Contributions</title><title>IEEE geoscience and remote sensing letters</title><addtitle>LGRS</addtitle><description>Accurate digital elevation model (DEM) estimation using synthetic aperture radar interferometry still remains a challenging problem in the geographical information science community, particularly in dealing with a high noise rate and atmospheric disturbances. 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| ispartof | IEEE geoscience and remote sensing letters, 2012-07, Vol.9 (4), p.764-768 |
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| subjects | Algorithms Atmospheric contributions Atmospheric modeling Atmospherics Bayesian methods Computer Science Dealing Discrete element method Disturbances Energy of formation Estimation graph cuts Image Processing Image reconstruction Joints multichannel phase unwrapping (PU) (MCPU) Optimization Surface topography Synthetic aperture radar synthetic aperture radar (SAR) interferometry (InSAR) |
| title | A Markovian Approach for DEM Estimation From Multiple InSAR Data With Atmospheric Contributions |
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