@conference {garbe2008c,
	title = {Measuring momentum transport directly at the air water interface from active infrared thermography},
	booktitle = {Geophysical Research Abstracts},
	year = {2008},
	author = {Christoph S. Garbe and Uwe Schimpf and Bernd J{\"a}hne}
}
@article {roetmann2007,
	title = {Micro-flow analysis by molecular tagging velocimetry and planar raman-scattering},
	journal = {Exp. Fluids},
	volume = {44},
	year = {2008},
	pages = {419--430},
	abstract = {The two dimensional Molecular Tagging Velocimetry (2D-MTV) was used to measure velocity fields of the flow in a micro mixer. Instead of commonly used micro particles an optical tagging of the flow was performed by using a caged dye. The flow induces a deformation of the optically written pattern that can be tracked by laser induced fluorescence. The series of raw images gained this way were analyzed quantitatively with a novel optical flow based technique. Reference measurements have been carried out allowing to draw conclusions about the accuracy of this procedure. A comparison to the standard technique of uPIV was also conducted. Apart from measuring flow velocities in microfluidic mixing processes, the spatial distribution of concentration fields for different species were also measured. To this end, a new technique has been developed that allows spatial measurements from Planar Spontaneous Raman Scattering (PSRS). The Raman stray light of the relevant species was spectrally selected by a narrow bandpass filter and thus detected unaffectedly by the Raman stray light of other species. The successful operation of this measurement procedure in micro flows will be demonstrated exemplary for a mixing process of water and ethanol.},
	doi = {10.1007/s00348-007-0420-1},
	author = {Karsten Roetmann and Waldemar Schmunk and Christoph S. Garbe and Volker Beushausen}
}
@conference {kondermann2008b,
	title = {Motion Estimation Based on a Temporal Model of Fluid Flows},
	booktitle = {13th International Symposium on Flow Visualization},
	year = {2008},
	pages = {1-10},
	author = {Daniel Kondermann and Claudia Kondermann and A. Berthe and U. Kertzscher and Christoph S. Garbe}
}
@phdthesis {garbe2007a,
	title = {Measuring and Modeling Fluid Dynamic Processes using Digital Image Sequence Analysis},
	year = {2007},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	author = {Christoph S. Garbe}
}
@conference {roetmann2006a,
	title = {Micro-flow analysis by molecular tagging velocimetry and planar Raman-scattering},
	booktitle = {Proc.\ of 12th International Symposium on Flow Visualization},
	year = {2006},
	author = {Karsten Roetmann and Christoph S. Garbe and Waldemar Schmunk and Volker Beushausen}
}
@conference {garbe2002b,
	title = {Measuring important parameters for air-sea heat exchange},
	booktitle = {ThermoSense},
	volume = {4710},
	year = {2002},
	pages = {171--182},
	publisher = {SPIE},
	organization = {SPIE},
	doi = {10.1117/12.459564},
	author = {Christoph S. Garbe and Uwe Schimpf and Bernd J{\"a}hne},
	editor = {Maldague, X. P. and Rozlosnik, A. E.}
}
@conference {garbe2002a,
	title = {Measuring the sea surface heat flux and probability distribution of surface renewal events},
	booktitle = {Gas Transfer at Water Surfaces},
	volume = {127},
	year = {2002},
	pages = {109-114},
	publisher = {American Geophysical Union},
	organization = {American Geophysical Union},
	doi = {10.1029/GM127p0109},
	author = {Christoph S. Garbe and Horst Hau{\ss}ecker and Bernd J{\"a}hne},
	editor = {E. S. Saltzman and M. A. Donelan and R. Wanninkhof and W. M. Drennan}
}
@conference {garbe2002e,
	title = {Mixed OLS-TLS for the estimation of dynamic processes with a linear source term},
	booktitle = {Proceedings of the 24th DAGM Symposium on Pattern Recognition},
	volume = {2449},
	year = {2002},
	pages = {463--471},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	abstract = {We present a novel technique to eliminate strong biases in parameter estimation were part of the data matrix is not corrupted by errors. Problems of this type occur in the simultaneous estimation of optical flow and the parameter of linear brightness change as well as in range flow estimation. For attaining highly accurate optical flow estimations under real world situations as required by a number of scientific applications, the standard brightness change constraint equation is violated. Very often the brightness change has to be modelled by a linear source term. In this problem as well as in range flow estimation, part of the data term consists of an exactly known constant. Total least squares (TLS) assumes the error in the data terms to be identically distributed, thus leading to strong biases in the equations at hand. The approach presented in this paper is based on a mixture of ordinary least squares (OLS) and total least squares, thus resolving the bias encountered in TLS alone. Apart from a thorough performance analysis of the novel estimator, a number of applications are presented.},
	doi = {10.1007/3-540-45783-6_56},
	author = {Christoph S. Garbe and Hagen Spies and Bernd J{\"a}hne},
	editor = {Luc Van Gool}
}
@phdthesis {garbe2001,
	title = {Measuring Heat Exchange Processes at the Air--Water Interface from Thermographic Image Sequence Analysis},
	year = {2001},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	abstract = {In this thesis a novel technique for estimating heat transfer at the free air water interface is presented. For the first time spatially resolved heat flux and transfer velocity measurements are available with a high temporal resolution. The statistical properties of the transfer processes are deduced and the parameters characterizing them established. Based on this analysis a second way to estimate the heat flux is presented. These techniques are based on thermal image sequences on which a motion analysis is performed. The motion is modelled in a general parameterization and physically motivated intensity changes can be incorporated by means of linear partial differential equations. In the presented framework the parameters of physical processes described by such differential equations can be estimated in multidimensional data. These general equations of motion are solved simultaneously by a method of least squares. To do so algorithms are developed that allow for unbiased estimates taking the structure of the noise into account. Methods from robust statistics are employed to correctly solve the estimation problem regardless if the data is corrupted by outliers. The relevance of the developed techniques to other scientific applications is shown. In an accuracy analysis confidence bounds of the proposed algorithms are established and limitations revealed. Following an examination under controlled laboratory conditions in the Heidelberg Aeolotron, the techniques are successfully applied at an international field campaign.},
	url = {http://www.ub.uni-heidelberg.de/archiv/1875},
	author = {Christoph S. Garbe}
}
