Dr. Hanno Scharr

Dr. Hanno Scharr
Institute for Chemistry and Dynamics of the
Geosphere (ICG), Institute III: Phytosphere
Research Center Jülich GmbH
52425 Jülich, Germany
phone: +49 (0)2461-61-5701
H.Scharr@fz-juelich.de
Current position
Research Associate (HGF-Nachwuchswissenschaftler)
Date and place of birth
Sep 10, 1969 in Heilbronn, Germany
Nationality and Status
German, married, 2 sons
Education
Ruprecht-Karls-University Heidelberg
- Image Processing, 11/1996-05/2000
Ph.D. (German Dr. rer. nat.) 05/2000
Supervisors Prof. Dr. B. Jähne and Prof. Dr. G. Wittum
- Physics, 10/1990 – 09/1996
B.Sc. (German Vordiplom) 06/1992
M.Sc. (German Diplom) 09/1996
Supervisor Prof. Dr. B. Jähne
- Sports and Sports Science, 10/1992-09/1999
B.Sc. (German Zwischenprüfung) 06/1996
Justinus-Kerner-Gymnasium Weinsberg
- Abitur (Honours), 1989
Professional Experience
Senior Researcher at Intel Research, Santa Clara , USA, 08/2002 – 07/2003
Research Associate (HGF-Nachwuchswissenschaftler) at Research Centre Jülich,
Member of the Hermann von Helmholtz Association of National Research Centres
(HGF), Jülich, Germany, since 08/2001 (paused for research stay at Intel)
Research Associate at Interdisciplinary Center for Scientific Computing (IWR),
Heidelberg University, Germany, 11/1999 – 07/2001
Consulting as software engineer, Windows NT Application with MFC for Max-

Planck-Institute (MPI) for Nuclear Physics, Heidelberg, Germany 05/1998 – 06/1998
Final year project (Diplomarbeit) at ABB Corporate Research Center, Heidelberg,
Germany, 09/1995 – 08/1996
Scientific assistant (Wissenschaftliche Hilfskraft) as system administrator at the
Institute for Sports and Sports Science, Heidelberg University, Germany, 06/1995
– 06/1996
Consulting as software engineer for speech pattern recognition and databases at
IBM Research Center, Heidelberg, Germany, 02/1994 – 06/1995
Scholarship
Graduate Scholarship, Center of Excellence (Graduiertenkolleg) ”Modeling and Scientific
Computing in Mathematics and Natural Sciences”, at Interdisciplinary Center
for Scientific Computing IWR, University of Heidelberg, 11/1996 – 10/1999
Reviewing
International Conference on Computer Vision and Pattern Recognition, CVPR
2003, CVPR 2004
IEEE Transactions on Image Processing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computing and Visualization in Science
Other Activities
Trainer and backstage manager at the children and youth circus ”Peperoni e.V.” in
Heidelberg (up to 120 children, honorary), 1993 – 2002
Carer of youth groups (up to 1200 children, during summer holidays, honorary,
Gaffenberg Heilbronn and other Groups), 1989 – 1998
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Research Interests
My research is focused on quantitative image and image sequence processing as an
analysis tool for scientific, medical and industrial data.
In typical applications detailed and accurate physical, biological, medical or tech-
nical models of the observed objects are available. Unfortunately, in most cases
acquired images do not directly reveal the object properties of interest. In addi-
tion scientific, medical or industrial imaging often operates at the sensor sensitivity
limit and thus the acquired data suffers from noise. Therefore the general prob-
lem addressed in my research is parameter estimation – i.e. measurement of object
properties – in corrupted or noisy multidimensional data.
Theoretical basis of this are fast, robust and highly accurate estimation algorithms
as well as discretizations of partial differential equations and their statistical moti-
vation. Parameter estimation here has to be understood as a physical measurement
process where error analysis is of highest importance in order to quantify the re-
liability of results. Systematical errors have to be minimized, e.g. by the use of
optimized filters and the choice of appropriate numerical estimation schemes. Sta-
tistical errors due to noise can be reduced by data-driven, nonlinear regularizations.
For practical applicability of these schemes, and thus for medical or industrial rel-
evance, a few requirements have to be met. Application specific parameters should
be automatically set wherever possible in order to make high end methods available
to non-expert users. This is a major challenge for most advanced algorithms, as
optimal parameter settings are hard to find in nonlinear systems and, what is more,
wrong settings can spoil the results. Besides this automation the algorithms have
to be implemented reliable, fast, modular, well tested, well documented and they
should be available on all standard computer platforms. Thus a mandatory inter-
est is the development of a software library providing a flexible image processing
toolbox.
This generality and flexibility open a wide range of applications. Among my previ-
ous and current projects are
• motion estimation in fluorescent microscopic image sequences of muscle motor
proteins (cooperation with Institute of Physiology and Pathophysiology, Univ.
Heidelberg),
• 2d texture analysis of paper formation (with ABB Research Center Heidel-
berg),
• 3d material testing of helicopter rotors in x-ray tomographic images (with
Eurocopter),
• quantitative growth and combined 3D-shape estimation of plant leaves (with
Research Center Jülich GmbH)
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• motion estimation and quantitative growth analysis of plant roots in mul-
tichannel, volumetric confocal microscopy image sequences (with Research
Center Jülich GmbH),
• 3d-shape reconstruction of plant leaves, wind generated water waves and in au-
tomotive applications, using binocular and multi-camera data (with Research
Center Jülich GmbH, Institute of Environmental Physics, Univ. Heidelberg
and Bosch)
• laser-diagnostic measurements and flame front analysis in combustion engines
(with Institute for Physical Chemistry, Univ. Heidelberg),
• reconstruction and analysis of silicon nano-structures in computer chips (with
Intel Research and Brown University).
Although they all fit seamlessly in the general framework of parameter estimation,
the special demands of each of these projects gave fruitful input for the development
of novel algorithms. Thus a major part of my image processing research is the tight
cooperation with scientists and engineers in a variety of disciplines, as apparent
from my current and former positions and cooperations.
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Publications
Theses
[1] H. Scharr. Optimal Operators in Digital Image Processing. PhD thesis, Interdisciplinary
Center for Scientific Computing, Ruprecht-Karls-Universität Heidelberg,
2000.
[2] H. Scharr. Digitale Bildverarbeitung und Papier: Texturanalyse mittels Pyramiden
und Grauwertstatistiken am Beispiel der Papierformation. Master’s thesis,
Fakultät für Physik und Astronomie, Ruprecht-Karls-Universität Heidelberg,
1996.
Book Chapters
[3] H. Scharr and B. Jähne. Optimization of spatio-temporal filter families for fast
and accurate motion estimation. In Image Sequence Analysis to Investigate
Dynamic Processes, Lecture Notes in Computer Science. Springer, accepted.
[4] H. Scharr, H. Spies, D. Uttenweiler, and B. Jähne. Noise suppression for image
sequence analysis by spatiotemporal anisotropic diffusion. In Image Sequence
Analysis to Investigate Dynamic Processes, Lecture Notes in Computer Science.
Springer, accepted.
[5] H. Haussecker, D. Fleet, B. Jähne, C. Garbe, H. Scharr, and H. Spies. A new
framework for imagesequence analysis: optical flow with physics-based brightness
models. In Image Sequence Analysis to Investigate Dynamic Processes,
Lecture Notes in Computer Science. Springer, accepted.
[6] H. Spies, C. Garbe, H. Haussecker, H. Scharr, M. Wenig, and B. Jähne. Flexible
regularization schemes. In Image Sequence Analysis to Investigate Dynamic
Processes, Lecture Notes in Computer Science. Springer, accepted.
[7] H. Spies, H. Scharr, M. Stöhr, R. Küsters, and T. Dierig. Motion in depth
and volumetric image sequences. In Image Sequence Analysis to Investigate
Dynamic Processes, Lecture Notes in Computer Science. Springer, accepted.
[8] F. Raisch, H. Scharr, and B. Jähne. Combining local and global motion estimation
via snakes. In Image Sequence Analysis to Investigate Dynamic Processes,
Lecture Notes in Computer Science. Springer, accepted.
[9] A. Walter, U. Schurr, S. Terjung, D. Schmundt, N. Kirchgessner, R. Küsters,
H. Spies, and H. Scharr. Analysis of growth processes in plant leaves and plant
roots. In Image Sequence Analysis to Investigate Dynamic Processes, Lecture
Notes in Computer Science. Springer, accepted.
[10] D. Uttenweiler, M. Vogel, T. Ober, H. Haussecker, H. Scharr, F. Raisch,
C. Veigel, and R.H.A. Fink. The dynamics of motor proteins: motion analysis
in high resolution fluorescence microscopic image sequences. In Image Sequence
Analysis to Investigate Dynamic Processes, Lecture Notes in Computer Science.
Springer, accepted.
[11] B. Jähne, H. Scharr, and S. Körkel. Principles of filter design. In Handbook of
Computer Vision and Applications. Academic Press, 1999.
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Refereed Articles
[12] D. Uttenweiler, C. Weber, B. Jähne, R.H.A. Fink, and H. Scharr. Spatiotemporal
anisotropic diffusion filtering to improve signal-to-noise ratios and object
restoration in fluorescence microscopic image sequences. Journal of Biomedical
Optics, 8(1):40–47, Jan. 2003. see also [13].
[13] D. Uttenweiler, C. Weber, B. Jähne, R.H.A. Fink, and H. Scharr. Spatiotemporal
anisotropic diffusion filtering to improve signal-to-noise ratios and object
restoration in fluorescence microscopic image sequences. Virtual Journal of
Biological Physics Research, Jan. 15 2003. see also [12].
[14] H. Scharr, M. Felsberg, and P.E. Forssén. Noise adaptive channel smoothing
of low-dose images. In Workshop Computer Vision for the Nano-Scale,
CVPR2003, 2003.
[15] H. Scharr, M.J. Black, and H.W. Haussecker. Image statistics and anisotropic
diffusion. In ICCV 2003, 2003.
[16] J. Weickert and H. Scharr. A scheme for coherence-enhancing diffusion filtering
with optimized rotation invariance. Journal of Visual Communication and
Image Representation, Special Issue On Partial Differential Equations In Image
Processing, Computer Vision, And Computer Graphics, pages 103–118, 2002.
[17] H. Scharr and R. Küsters. A linear model for simultaneous estimation of
3d motion and depth. In IEEE Workshop on Motion and Video Computing,
Orlando, Florida, USA, December 5-6 2002.
[18] N. Kirchgeßner, H. Scharr, and U. Schurr. Robust vein extraction on plant leaf
images. In 2nd IASTED International Conference Visualization, Imaging and
Image Processing (VIIP 2002), Malaga, Spain, September 9-12 2002.
[19] F. Raisch, H. Scharr, B. Jähne, and D. Uttenweiler. Active contour segmentation
in noisy fluorescence image sequences. In 2nd IASTED International
Conference Visualization, Imaging and Image Processing (VIIP 2002), Malaga,
Spain, September 9-12 2002.
[20] H. Scharr and R. Küsters. Simultaneous estimation of motion and disparity:
Comparison of 2-, 3- and 5-camera setups. In 2nd IASTED International
Conference Visualization, Imaging and Image Processing (VIIP 2002), Malaga,
Spain, September 9-12 2002.
[21] M. Diehl, R. Küsters, and H. Scharr. Simultaneous estimation of local and
global parameters in image sequences. In 4. Workshop Dynamic Perception,
Bochum, Germany, 14-15 November 2002.
[22] J. Gronki, C. Schulz, and H. Scharr. Correction of beam steering effects in 2dlaser-diagnostic
measurements in combustion engines by image postprocessing.
In Eurotherm 2002, Seminar 71: Visualization, imaging and data analysis in
convective heat and mass transfer, Reims, France, October 28-30 2002.
[23] U. Schurr, A. Walter, S. Wilms, H. Spies, N. Kirchgessner, H. Scharr, and
R. Küsters. Dynamics of leaf and root growth. In 12th International Congress
on Photosynthesis, PS 2001, Brisbane Convention & Exhibition Centre, Brisbane,
Australia, 2001.
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[24] H. Scharr and D. Uttenweiler. 3d anisotropic diffusion filtering for enhancing
noisy actin filament fluorescence images. In DAGM 2001, pages 69–75,
September 2001.
[25] N. Kirchgeßner, H. Spies, H. Scharr, and U. Schurr. Root growth measurements
in object coordinates. In DAGM 2001, pages 231–238, September 2001.
[26] N. Kirchgeßner, H. Spies, H. Scharr, and U. Schurr. Root growth analysis in
physiological coordinates. In ICIAP 2001, September 2001.
[27] H. Spies and H. Scharr. Accurate optical flow in noisy image sequences. In
ICCV 2001, Vancouver, Canada, 2001.
[28] H. Scharr, B. Jähne, S. Böckle, J. Kazenwadel, T. Kunzelmann, and C. Schulz.
Flame front analysis in turbulent combustion. In DAGM 2000, Mustererkennung
2000, Informatik aktuell, pages 325–332. Springer, 2000.
[29] H. Scharr and J. Weickert. An anisotropic diffusion algorithm with optimized
rotation invariance. In DAGM 2000, September 2000.
[30] H. Spies, N. Kirchgeßner, H. Scharr, and B. Jähne. Dense structure estimation
via regularised optical flow. In Vision, Modeling, And Visualization 2000,
Saarbrücken, 2000. Max-Planck-Institut für Informatik, Saarbrücken, Germany
in cooperation with IEEE Signal Processing Society, Gesellschaft für Informatik
GI.
[31] N. Kirchgeßner, H. Scharr, and U. Schurr. 3D-Modellierung von
Pflanzenblättern mittels eines Depth-from-Motion Verfahrens. In DAGM 2000,
pages 381–388, 2000.
[32] B. Jähne, H. Haußecker, H. Scharr, H. Spies, D. Schmundt, and U. Schurr.
Study of dynamical processes with tensor-based spatiotemporal image processing
techniques. In Computer Vision - ECCV ’98, pages 322–336. Springer-
Verlag, 1998.
[33] H. Scharr, S. Körkel, and B. Jähne. Numerische Isotropieoptimierung von
FIR-Filtern mittels Querglättung. In DAGM’97, pages 367–374, 1997.
Technical Reports
[34] H. Scharr. Optimization of spatiotemporal filter families for extended optical
flow. Technical report, Intel Research, 2003.
[35] M. Felsberg, H. Scharr, and P.E. Forssén. B-spline channel representation.
Technical report, Computer Vision Lab, Linköping, Sweden, 2002.
[36] H. Scharr, R. Küsters, A. Cavallo, S. Terjung, B. Jähne, and U. Schurr. Extended
optical flow in volume sequences: Unified framework and performance
evaluation. Technical report, DFG research unit ”Image Sequence Analysis to
Investigate Dynamic Processes”, 2002.
[37] H. Scharr. Binokulare Stereoverfahren: Ein Überblick mit dem Schwerpunkt
schnelle Algorithmen und Diskontinuitäten. Technical report, DFG research
unit ”Image Sequence Analysis to Investigate Dynamic Processes”, 2001.
[38] H. Scharr. Optimal separable interpolation of color images with bayer array
format. Technical report, DFG research unit ”Image Sequence Analysis to
Investigate Dynamic Processes”, 2000.
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[39] H. Spies and H. Scharr. Robust optical flow computation in noisy image sequences
by anisotropic diffusion. Technical report, DFG research unit ”Image
Sequence Analysis to Investigate Dynamic Processes”, 2000.
[40] J. Weickert and H. Scharr. A scheme for coherence-enhancing diffusion filtering
with optimized rotation invariance. Technical report, Fakultät für Mathematik
und Informatik, Universität Mannheim, 2000.
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