@incollection {garbe_08_nonlinear,
	title = {Nonlinear Analysis of Multi-Dimensional Signals},
	year = {2008},
	note = {1},
	pages = {231-288},
	publisher = {Springer},
	doi = {10.1007/978-3-540-75632-3_7},
	author = {Christoph S. Garbe and Kai Krajsek and Pavel Pavlov and Bj{\"o}rn Andres and Matthias M{\"u}hlich and Ingo Stuke and Cicero Mota and Martin B{\"o}hme and Martin Haker and Schuchert, T. and Hanno Scharr and Til Aach and Erhardt Barth},
	editor = {R. Dahlhaus and J. Kurths and Timmer, J. and Peter Maass}
}
@incollection {garbe2008,
	title = {Nonlinear analysis of multi-dimensional signals: local adaptive estimation of complex motion and orientation patterns},
	year = {2008},
	pages = {231-288},
	publisher = {Springer},
	abstract = {We consider the general task of accurately detecting and quantifying orientations in n-dimensional signals s. The main emphasis will be placed on the estimation of motion, which can be thought of as orientation in spatiotemporal signals. Associated problems such as the optimization of matched kernels for deriving isotropic and highly accurate gradients from the signals, optimal integration of local models, and local model selection will also be addressed.},
	doi = {10.1007/978-3-540-75632-3_7},
	author = {Christoph S. Garbe and Kai Krajsek and Pavel Pavlov and Bj{\"o}rn Andres and Matthias M{\"u}hlich and Ingo Stuke and Cicero Mota and Martin B{\"o}hme and Martin Haker and Tobias Schucher and Hanno Scharr and Til Aach and Erhardt Barth},
	editor = {R. Dahlhaus and J. Kurths and Timmer, J. and Peter Maass}
}
@book {jaehne2007a,
	title = {Complex Motion, Proceedings of the 1st Workshop, G{\"u}nzburg, October 2004},
	volume = {3417},
	year = {2007},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-540-69866-1},
	author = {Bernd J{\"a}hne},
	editor = {Mester, R. and Hanno Scharr and Erhardt Barth}
}
@conference {scharr2002,
	title = {A linear model for simultaneous estimation of 3D motion and depth},
	booktitle = {Proceedins of IEEE Workshop on Motion and Video Computing 2002, Orlando},
	year = {2002},
	doi = {10.1109/MOTION.2002.1182240},
	author = {Hanno Scharr and K{\"u}sters, R.}
}
@conference {raisch2002,
	title = {Velocity and feature estimation of actin filaments using active contours in noisy fluorescence image sequences},
	booktitle = {Proc. 2nd IASTED Int. Conf. Visualization, Imaging and Image Processing},
	year = {2002},
	pages = {645--650},
	abstract = {We present a new approach for determining particle fea tures such as length, curvature and hence flexibility in addition to the velocity of moving single actin filaments in noisy fluorescence image sequences. The reliable deter mination of these features is essential for the analysis of the elementary force generation process of single motor molecules including heart and skeletal muscle myosins. First, the image sequence is preprocessed with the 3D structure tensor - where the third dimension is the time t in the image sequence - in order to eliminate noise and to obtain a measure for extracting coherently moving par ticles. Secondly, we determine the contour of the actin filaments with subpixel accuracy using active contours. Thereafter, we readjust a local coordinate system to elim inate inner movements of the active contour. In the fourth step, we estimate the initial position of the active contour in the next frame from the displacement vector field cal culated by the 3D structure tensor. The accuracy of the method is verified on synthetic test data, a prerequisite for the quantitative use of this method on experimentally obtained data. Finally this is demonstrated for fluorescence image sequences of actin filament movement in the in vitro motility assay.},
	author = {Florian Raisch and Hanno Scharr and Norbert Kirchge{\ss}ner and Bernd J{\"a}hne and Rainer H. A. Fink and D. Uttenweiler}
}
@conference {spies2001d,
	title = {Accurate optical flow in noisy image sequences},
	booktitle = {ICCV},
	year = {2001},
	pages = {587--592},
	doi = {10.1109/ICCV.2001.937571},
	author = {Hagen Spies and Hanno Scharr}
}
@conference {kirchgessner2001,
	title = {Root Growth Analysis in Physiological Coordinates},
	booktitle = {International Conference on Image Analysis and Processing (ICIAP{\textquoteright}01)},
	year = {2001},
	author = {Norbert Kirchge{\ss}ner and Hagen Spies and Hanno Scharr and Ulrich Schurr}
}
@conference {kirchgessner2001a,
	title = {Root Growth Measurements in Object Coordinates},
	booktitle = {Proceedings of the 23th DAGM Symposium on Pattern Recognition},
	year = {2001},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/3-540-45404-7_31},
	author = {Norbert Kirchge{\ss}ner and Hagen Spies and Hanno Scharr and Ulrich Schurr}
}
@conference {kirchgessner2000,
	title = {3D-Modellierung von Pflan-zen-bl{\"a}t-tern mittels eines Depth-from-Motion Verfahrens},
	booktitle = {Proceedings of the 22th DAGM Symposium on Pattern Recognition},
	year = {2000},
	pages = {381--388},
	doi = {10.1007/978-3-642-59802-9_48},
	author = {Norbert Kirchge{\ss}ner and Hanno Scharr and Ulrich Schurr}
}
@conference {scharr2000a,
	title = {An anisotropic diffusion algorithm with optimized rotation invariance},
	booktitle = {Proceedings of the 22th DAGM Symposium on Pattern Recognition},
	year = {2000},
	pages = {460--467},
	doi = {10.1007/978-3-642-59802-9_58},
	author = {Hanno Scharr and Weickert, J.}
}
@conference {spies2000c,
	title = {Dense structure estimation via regularised optical flow},
	booktitle = {VMV 2000},
	year = {2000},
	pages = {57--64},
	publisher = {Aka GmbH, Berlin},
	organization = {Aka GmbH, Berlin},
	author = {Hagen Spies and Norbert Kirchge{\ss}ner and Hanno Scharr and Bernd J{\"a}hne},
	editor = {Girod, G. and Greiner, G. and Hans-Peter Seidel and H. Niemann}
}
@conference {scharr2000c,
	title = {Flame front analysis in turbulent combustion},
	booktitle = {Mustererkennung 2000},
	year = {2000},
	pages = {325--332},
	publisher = {Springer},
	organization = {Springer},
	doi = {10.1007/978-3-642-59802-9_41},
	author = {Hanno Scharr and Bernd J{\"a}hne and S. B{\"o}ckle and J. Kazenwadel and T. Kunzelmann and C. Schulz and N. Kr{\"u}ger},
	editor = {G. Sommer and Ch. Perwasser}
}
@techreport {scharr2000b,
	title = {Optimal separable interpolation of color images with bayer array format},
	year = {2000},
	institution = {DFG research unit Image Sequence Analysis to Investigate Dynamic Processes, Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany},
	url = {http://www.ub.uni-heidelberg.de/archiv/12680/},
	author = {Hanno Scharr}
}
@phdthesis {scharr2000,
	title = {Optimale Operatoren in der Digitalen Bildverarbeitung},
	year = {2000},
	publisher = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	abstract = {A novel method for optimal choice of filter operators is presented. Single filters as well as filter families with linear or nonlinear optimal criteria can be addressed by different weighted norms in wave number domain. Coefficients of filters with arbitrary support can be optimized in floating point or fixed point accuracy. Numerous examples are presented to illustrate optimization of filters e.g by isotropy, rotation invariance or accuracy of absolute value, and each is followed by discussions of results. Errors are decreased by up to 3 orders of magnitude compared to standard parameter choices. In an investigation of displacements calculated by the well known structure tensor approach with optimal filters the results are improved in two respects. Firstly, estimation errors are decreased by approximately two orders of magnitude and secondly, they are more robust with respect to noise. The greatly improved performance is demonstrated by a tracking application. A novel explicit discretization for anisotropic diffusion filtering using optimal filters is introduced. Numerical errors of this scheme obtained by comparison with a novel analytical solution are about 1.5 to 2.5 orders of magnitude smaller than the errors introduced by the best comparable standard method. The new method clearly outperforms the latter in a reconstruction test. Due to the higher stability with respect to larger time steps, the new method is 3 to 4 times faster than other explicit schemes.},
	url = {http://www.ub.uni-heidelberg.de/archiv/962},
	author = {Hanno Scharr}
}
@incollection {jaehne1999k,
	title = {Principles of Filter Design},
	volume = {2},
	year = {1999},
	pages = {125--151},
	publisher = {Academic Press},
	author = {Bernd J{\"a}hne and Hanno Scharr and K{\"o}rkel, S. and Bernd J{\"a}hne and Horst Hau{\ss}ecker and Peter Gei{\ss}ler}
}
@conference {jaehne1998b,
	title = {Study of dynamical processes with tensor-based spatiotemporal image processing techniques},
	booktitle = {ECCV 1998},
	volume = {1407},
	year = {1998},
	pages = {322--336},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Image sequence processing techniques are used to study exchange, growth, and transport processes and to tackle key questions in environmental physics and biology. These applications require high accuracy for the estimation of the motion field since the most interesting parameters of the dynamical processes studied are contained in first-order derivatives of the motion field or in dynamical changes of the moving objects. Therefore the performance and optimization of low-level motion estimators is discussed. A tensor method tuned with carefully optimized derivative filters yields reliable and dense displacement vector fields (DVF) with an accuracy of up to a few hundredth pixels/frame for real-world images. The accuracy of the tensor method is verified with computer-generated sequences and a calibrated image sequence. With the improvements in accuracy the motion estimation is now rather limited by imperfections in the CCD sensors, especially the spatial nonuniformity in the responsivity. With a simple two-point calibration, these effects can efficiently be suppressed. The application of the techniques to the analysis of plant growth, to ocean surface microturbulence in IR image sequences, and to sediment transport is demonstrated.},
	doi = {10.1007/BFb0054750},
	author = {Bernd J{\"a}hne and Horst Hau{\ss}ecker and Hanno Scharr and Hagen Spies and Dominik Schmund and Ulrich Schurr}
}
@conference {scharr1997,
	title = {Numerische Isotropieoptimierung von FIR-Filtern mittels Quergl{\"a}ttung},
	booktitle = {Proceedings of the 19th DAGM Symposium on Pattern Recognition, Braunschweig},
	year = {1997},
	pages = {199--208},
	doi = {10.1007/978-3-642-60893-3_39},
	author = {Hanno Scharr and K{\"o}rkel, S. and Bernd J{\"a}hne},
	editor = {E. Paulus and F. M. Wahl}
}
@mastersthesis {scharr1996,
	title = {Digitale Bildverarbeitung und Papier Texturanalyse mittels Pyramiden und Grauwertstatistiken am Beispiel der Papierformation},
	year = {1996},
	school = {IWR, Fakult{\"a}t f{\"u}r Physik und Astronomie, Univ.\ Heidelberg},
	abstract = {Bei der Beurteilung der Qualit{\"a}t von Papier ist die G{\"u}te der Formation ein wichtiges Kriterium. Definitionsgem{\"a}{\ss}, nach ISO-Norm 4046-1978, versteht man unter Formation die Art und Weise, wie Fasern verteilt, angeordnet und vermischt sind, um ein Papier zu bilden [Praast und G{\"o}ttsching, 1991]. F{\"u}r Papiermacher und -verarbeiter ist die Formation die Verteilung von hellen und dunklen Flecken, Wolken bzw. Flocken die man sieht, wenn man ein unbedrucktes Blatt Papier gegen das Licht h{\"a}lt (siehe auch [Bolam, 1961]). Die beiden ausschlaggebenden Merkmale sind die mittlere Flockengr{\"o}{\ss}e und ihr Kontrast gegen den Hintergrund. Visuell ist die G{\"u}te der Massenverteilung auch f{\"u}r den Laien z.B. mittels paarweisem Vergleich (PV) der Proben einfach und zuverl{\"a}ssig durchzuf{\"u}hren (siehe [Hradezky, 1977]). Bisher k{\"o}nnen industrielle Formationsme{\ss}ger{\"a}te den Kontrast sehr gut, aber die Flockengr{\"o}{\ss}e nur relativ unzuverl{\"a}ssig bestimmen. Zudem sind die zuverl{\"a}ssigsten Methoden sehr rechenintensiv.},
	author = {Hanno Scharr}
}
