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Integrated denoising and unwrapping of INSAR phase based on Markov random fields / Runpu Chen in IEEE Transactions on geoscience and remote sensing, vol 51 n° 8 (August 2013)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 51 n° 8 (August 2013) . - pp 4473 - 4485 Titre : Integrated denoising and unwrapping of INSAR phase based on Markov random fields Type de document : Article/Communication Auteurs : Runpu Chen, Auteur ; Weidong Yu, Auteur ; Robert Wang, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 4473 - 4485 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] champ aléatoire de Markov [Termes IGN] filtrage du bruit [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] phase [Termes IGN] reconstruction d'image [Termes IGN] restauration d'image Résumé : (Auteur) In the traditional processing flow of interferometric synthetic aperture radar (SAR) technique, the processing of phase is conducted via two separated and successive steps, i.e., phase denoising and phase unwrapping. That is to say, first, wrapped phases without noise are generated, and then, the true phases without 2?-ambiguities are reconstructed (here and in the rest of this paper, true phase refers to the information-induced unwrapped phase without noise). Such separated steps will inevitably bring in extra estimation error because each step has necessary approximations and presumptions which do not always hold. On the contrary, in this paper, we treat phase denoising and unwrapping as a single problem of true phase recovery from observed ones. Following this methodology, an integrated phase denoising and unwrapping algorithm based upon Markov random fields (MRFs) is proposed. Taking a priori knowledge of interferometric phases into account, MRF is used to model the relationship between the elements in the random variable set including both true phases and their observations. After the model is built up, the energy function of this MRF is defined according to the local-independence property inferred from the MRF structure and then minimized to obtain the estimate of the true phase value. In the end of this paper, experiments on simulated and true phase data are conducted, and the comparison with several commonly used unwrapping methods is proposed to verify the efficiency of the proposed MRF algorithm. Numéro de notice : A2013-419 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2268969 En ligne : https://doi.org/10.1109/TGRS.2013.2268969 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32557 [article]

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