Estimating Apparent Motion on Satellite Acquisitions with a Physical Dynamic Model

Huot, Etienne; Herlin, Isabelle; Mercier, Nicolas; Plotnikov, Evgeny

doi:10.1109/icpr.2010.19

Cited by 6 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These methods consider a hidden state to represent the field that has to be estimated, a dynamic model for the state, and a measurement model that links the state with the observation. Hence, the popular 4D-Var approach has been used in [12] for estimating the ocean surface velocity field. This technique uses Sea surface Temperature (SST) images and consider an Extended Image Model driven by a shallow water approximation for the dynamics of the velocity field.…”

Section: A Image Assimilationmentioning

confidence: 99%

Data assimilation with state alignment using high-level image structures detection

Makris

Papadakis

2012

2012 International Conference on Computer Vision in Remote Sensing

View full text Add to dashboard Cite

International audienceSequential and variational assimilation methods allow tracking physical states using dynamic prior together with external observation of the studied system. However, when dense image satellite observations are available, such approaches realize a correction of the amplitude of the different state values but do not incorporate the spatial errors of structure positions. In the case of the position of a vortex, for example, when there is misfit between state and observation, the processes can be long to converge and even diverge when high dimensional state spaces are treated with few iterations of the assimilation methods as it is the case in operational algorithms. In this paper, we tackle this issue by proposing an alignment method based on modern object detection methods that uses visual correspondences between the physical state model and the structural information given by a sequence of image observing the phenomena

show abstract

Section: A Image Assimilationmentioning

confidence: 99%

Data assimilation with state alignment using high-level image structures detection

Makris

Papadakis

2012

2012 International Conference on Computer Vision in Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Among those heuristics, the shallow water model [17] has been proven to be suitable for representing the surface circulation of closed seas, such as Black Sea [10]. These shallow water equations have also been successfully used to estimate the upper layer circulation of Black Sea from Sea Surface Temperature (SST) images [5,6] with a data assimilation method.…”

Section: Introductionmentioning

confidence: 99%

Coupling Dynamic Equations and Satellite Images for Modelling Ocean Surface Circulation

Béréziat

Herlin

2015

Communications in Computer and Information Science

Self Cite

View full text Add to dashboard Cite

Abstract. Satellite image sequences visualise the ocean surface and allow assessing its dynamics. Processing these data is then of major interest to get a better understanding of the observed processes. As demonstrated by state-of-the-art, image assimilation permits to retrieve surface motion, based on assumptions on the dynamics. In this paper, we demonstrate that a simple heuristics, such as the Lagrangian constancy of velocity, can be used and successfully replace the complex physical properties described by the Navier-Stokes equations for assessing surface circulation from satellite images. A data assimilation method is proposed that adds an acceleration term a(t) to this Lagrangian constancy equation, which summarises all physical processes other than advection. A cost function is designed that quantifies discrepancy between satellite data and model values. This cost function is minimised by the BFGS solver with a dual method of data assimilation. The result is the initial motion field and the acceleration terms a(t) on the whole temporal interval. These values a(t) model the forces, other than advection, that contribute to surface circulation. Our approach was tested on synthetic data and with Sea Surface Temperature images acquired on Black Sea. Results are quantified and compared to those of state-of-the-art methods.

show abstract

“…This 2D model has been proven to be suitable for representing the surface circulation of closed seas, such as Black Sea (Oguz et al, 1992). The shallow water equations have also been success-1 http://www.nemo-ocean.eu/ fully used to estimate the upper layer circulation of Black Sea from Sea Surface Temperature (SST) images (Korotaev et al, 2008;Huot et al, 2010) with a data assimilation method.…”

Section: Introductionmentioning

confidence: 99%

Image-based Modelling of Ocean Surface Circulation from Satellite Acquisitions

Béréziat

Herlin

2014

Proceedings of the 9th International Conference on Computer Vision Theory and Applications

View full text Add to dashboard Cite

To cite this version:Satellite image sequences permit to visualise oceans' surface and their underlying dynamics. Processing these images is then of major interest in order to better understanding of the observed processes. As demonstrated by state-of-the-art, image assimilation allows to retrieve surface motion from image sequences, based on assumptions on the dynamics. In this paper we demonstrate that a simple heuristics, such as the Lagrangian constancy of velocity, can be used, and successfully replaces the complex physical properties described by the Navier-Stokes equations, for assessing surface circulation from satellite images. A data assimilation method is proposed that includes an additional term a(t) to this Lagrangian constancy equation. That term summarises all physical processes other than advection. A cost function is designed, which quantifies discrepancy between satellite data and model values. The cost function is minimised by the BFGS solver with a dual method of data assimilation. The result is the motion field and the additional term a(t). This last component models the forces, other than advection, that contribute to surface circulation. The approach has been tested on Sea Surface Temperature of Black Sea. Results are given on four image sequences and compared with state-ofthe-art methods.

show abstract

Estimating Apparent Motion on Satellite Acquisitions with a Physical Dynamic Model

Cited by 6 publications

References 10 publications

Data assimilation with state alignment using high-level image structures detection

Data assimilation with state alignment using high-level image structures detection

Coupling Dynamic Equations and Satellite Images for Modelling Ocean Surface Circulation

Image-based Modelling of Ocean Surface Circulation from Satellite Acquisitions

Contact Info

Product

Resources

About