A Markovian Approach for DEM Estimation From Multiple InSAR Data With Atmospheric Contributions

• Published in: IEEE geoscience and remote sensing letters Vol. 9; no. 4; pp. 764 - 768
• Main Authors: Shabou, A., Tupin, F.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2012; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); IEEE - Institute of Electrical and Electronics Engineers
• 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); data fusion; markovian model; interferometry
• ISSN: 1545-598X; 1558-0571
• DOI: 10.1109/LGRS.2011.2181326

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.