Image Analysis Group

Prof. Dr. Gabriele Steidl

Address

Paul-Ehrlich-Straße
building 31 , room 452
67663 Kaiserslautern

P.O. Box 3049
67653 Kaiserslautern

Contact

Tel.: +49 631 205 5320
Fax: +49 631 205 5309
E-Mail: steidl@mathematik.uni-kl.de


Research interests

  • Applied and Computational Harmonic Analysis
  • Convex Analysis and Optimization
  • Image Processing

Books

G. Plonka, D. Potts, G. Steidl, M. Tasche.
Numerical Fourier Analysis.
Harmonic and Applied Analysis. 1-573, Birkhäuser 2019.
[www]

Publications sorted by years

  • M. Hasanasab, J. Hertrich, F. Laus and Gabriele Steidl, (2019)
    Alternatives of the EM algorithm for estimating the parameters of the Student-t distribution
    (arXiv Preprint#1910.06623)
    [www]

  • M. Ehler, M. Gräf, S. Neumayer and G. Steidl, (2019)
    Curve based approximation of measures on manifolds by discrepancy minimization
    (arXiv Preprint#1910.06124)
    [www]

  • M. Hasannasab, S. Neumayer G. Plonka, S. Setzer, G. Steidl  and J. Geppert, (2019)
    Frame soft shrinkage as proximity operator
    (arXiv Preprint#1910.02843)
    [www]

  • R. Bergmann, F. Laus, J. Persch, G. Steidl, (2018)
    Recent advances in denoising of manifold-valued images
    (arXiv Preprint#1812.05594)
    [www]

  • M. Bačák, J. Hertrich, S. Neumayer, G. Steidl (2019).
    Minimal Lipschitz and ∞-Harmonic Extensions of Vector-Valued Functions on Finite Graphs
    (arXiv Preprint #1903.04873)
    [arxiv]

  • Ole Christensen, Marzieh Hasannasab, Gabriele Steidl (2019)
    On approximate operator representations of sequences in Banach spaces,
    submitted


      • X. Cai, R. Chan, C.-B. Schönlieb, G. Steidl, T. Zeng, (2018)
        Linkage between piecewise constand Mumfor-Shah model and ROF model and its virtue in image segmentation
        SIAM Journal on Imaging Sciences
        (arXiv Preprint#1807.10194)
        [www]

      • S. Neumayer,  M. Nimmer, S. Setzer, G. Steidl, (2019)
        On the rotational invariant L_1-norm PCA
        Linear Algebra and its Applications
        (arXiv Preprint#1902.03840)
        [www]

      • F. Laus, G. Steidl, (2019).
        Multivariate myriad filters based on parameter estimation of Student-t distributions
        SIAM Journal on Imaging Sciences
        (arXiv Preprint#1810.05594)
        [www]

      • J. Lellmann, S. Neumayer, M. Nimmer, G. Steidl, (2019)
        Methods for finding the offset in robust subspace fitting
        PAMM, 19(1)
      •  S. Neumayer,  M. Nimmer, S. Setzer, G. Steidl, (2019)
        On the robust PCA and Weiszfeld's algorithm
        Applied Mathematics and Optimization,
        (arXiv Preprint#1902.04292)
        [www]

      2019

      • S. Neumayer, J. Persch, G. Steidl (2019).
        Regularization of inverse problems via time discrete geodesics in image spaces.
        Inverse Problems, 35 (5)
        [www]
      • D. Dobrovolskij, J. Persch, K. Schladitz and G. Steidl (2018).
        Structure detection with second order Riesz transforms.
        Image Analysis & Stereology, 38 (1), 107-119
      • S. Dahlke, F. De Mari, E. De Vito, L. Sawatzki, G. Steidl, G. Teschke, F. Voigtlaender (2018).
        On the atomic decomposition of coorbit spaces with non-integrable kernel.
        P. Boggiatto, E. Cordero, M. de Gosson, H. G. Feichtinger,  F. Nicola, A. Oliaro, A. Tabacco (eds.)
        Landscapes of Time-Frequency Analysis, 75-144, Birkhäuser 2018
        .
        [www]

      • J. Hertrich, M. Bačák, S. Neumayer, G. Steidl (2019).
        Minimal Lipschitz extensions for vector-valued functions on finite graphs.
        M. Burger, J. Lellmann and J. Modersitzki (eds.)
        Scale Space and Variational Methods in Computer Vision , LNCS

      • T. Batard, M. Bertalmio, G. Steidl (2019).
        A connection between image processing and artifi cial neural network layers through a
        geometric model of visual perception
        M. Burger, J. Lellmann and J. Modersitzki (eds.)
        Scale Space and Variational Methods in Computer Vision , LNCS

      • S. Dahlke, Q. Jahan, C. Schneider, G. Steidl, G. Teschke (2019).
        Traces of shearlet coorbit spaces on domains.
        Applied Mathematics Letters, 91, 35-40.
        [www]

      2018

      • R. Bergmann, J. H. Fitschen, J. Persch, G. Steidl (2018).
        Priors with coupled first and second order differences for manifold-valued image processing.
        Journal of Mathematical Imaging and Vision. 60, (9), 1459-1481.
        [www]
      • S. Neumayer, J. Persch, G. Steidl (2018).
        Morphing of manifold-valued images inspired by discrete geodesics in image spaces.
        SIAM Journal of Imaging Sciences. 11, (3), 1898-1930.
        [www] 

      • F. Laus, F. Pierre, G. Steidl (2018).
        Nonlocal myriad filters for Cauchy noise removal.
        Journal of Mathematical Imaging and Vision. 60, (8), 1324–1354.
        [doi] [www]

      • F. Balle, T. Beck, D. Eifler, J. H. Fitschen, S. Schuff, G. Steidl.
        Strain analysis by a total generalized variation regularized optical flow model.
        Inverse Problems in Science and Engineering.
        doi.org/10.1080/17415977.2018.1475479
        [www]

      • M. Nimmer, G. Steidl, R. Riesenberg, A. Wuttig (2018).
        Spectral imaging based on 2D diffraction patterns and a regularization model.
        Optics Express. 26, (22), 28335-28348, doi.org/10.1364/OE.26.028335
        [www]

      2017

      • F. Pierre, J.-F. Aujol, A. Bugeau, S. Steidl, V.-R. Ta (2017).
        Variational contrast enhancement of RGB images.
        Journal of Mathematical Imaging and Vision. 57, (1), 99-116.
        [www] 

      • M. Burger, A. Sawatzky, G. Steidl (2017).
        First order algorithms in variational image processing.
        R. Glowinski, S. Osher and W. Yin (eds.)
        Operator Splittings and Alternating Direction Methods, Springer 2017
        .
        [pdf] [www] 

      • S. Dahlke, F. De Mari, E. De Vito, D. Labate, G. Steidl, G. Teschke, S. Vigogna (2017).
        Coorbit spaces with voice in a Fréchet space.
        The Journal of Fourier Analysis and its Applications. 23, (1), 141-206.
        [pdf] [www] 

      • R. Bergmann, J. H. Fitschen J. Persch, G. Steidl (2017).
        Iterative multiplicative filters for data labeling.
        International Journal of Computer Vision. 123, (3), 123-145.
        [www] 

      • B. Bauer, X. Cai, S. Peth, K. Schladitz, G. Steidl (2017).
        Variational-based segmentation of biopores in tomographic images.
        Computers & Geosciences. 98, 1-8.
        [doi][www]

      • J. H. Fitschen, J. Ma, S. Schuff (2017).
        Removal of curtaining effects by a variational model with directional forward differences.
        Computer Vision and Image Understanding. 155, 24-32.
        [doi] [www] 

      • F. Laus, M. Nikolova, J. Persch, G. Steidl (2017).
        A nonlocal denoising algorithm for manifold-valued images using second order statistics.
        SIAM Journal on Imaging Sciences. 10, (1), 416–448.
        [doi] [www] 

      • J. H. Fitschen, K. Losch, G. Steidl (2017).
        Unsupervised multi class segmentation of 3D images with intensity inhomogeneities.
        Journal of Visual Communication and Image Representation. 46, 312-323.
        [doi] [www] 

      • R. Bergmann, J. H. Fitschen, J. Persch, G. Steidl (2017).
        Infimal convolution type coupling of first and second order differences on manifold-valued images.
        Scale Space and Variational Methods in Computer Vision. Lauze, Francois and Dong, Yiqiu and Dahl, Anders Bjorholm (eds.) Lecture Notes in Computer Science 10302, 447-459.
        [doi] [www] 
      • M. Bačák, M. Montag, G. Steidl (2017).
        Convergence of functions and their Moreau-Yosida envelopes on Hadamard spaces.
        Journal of Approximation Theory. 224, 1-12.
        [www] 

      • T. H. Loeber, B. Laegel, S. Wolff, S. Schuff, F. Balle, T. Beck, D. Eifler, J. H. Fitschen, G. Steidl (2017).
        Reducing curtaining effects in FIB/SEM applications by a goniometer stage and an image processing method.
        Journal of Vacuum Science & Technology B, Nanotechnology and Microelectronics: Materials, Processing, Measurement, and Phenomena 35.
        [doi] [www]

      • R. Bergmann, F. Laus, J. Persch, G. Steidl (2017).
        Manifold-valued image processing.
        Siam News. 50, (8), 1,3.
        [www] 

      • S. Neumayer, M. Nimmer and G. Steidl (2017).
        On a projected Weiszfeld algorithm.
        Scale Space and Variational Methods in Computer Vision. Lauze, Francois and Dong, Yiqiu and Dahl, Anders Bjorholm (eds.) Lecture Notes in Computer Science 10302, 486-497.
        [www] 
      • J. Persch, F. Pierre, G. Steidl (2017).
        Exemplar-based face colorization using image morphing.
        Journal of Imaging. 3, (4), Art.Num. 48.
        [doi] [www] 

      2016

      • R. Bergmann, R. H. Chan, R. Hielscher, J. Persch, G. Steidl (2016).
        Restoration of manifold-valued images by half-quadratic minimization.
        Inverse Problems and Imaging. 10, (2), 281–304.
        [doi] [www] 

      • M. Bačák, R. Bergmann, G. Steidl, A. Weinmann (2016).
        A Second order non-smooth variational model for restoring manifold-valued images.
        SIAM Journal on Scientific Computing. 38, (1), 567 - 597.
        [doi] [www] 

      • R. Bergmann, J. Persch, G. Steidl (2016).
        A parallel Douglas–Rachford algorithm for restoring images with values in symmetric Hadamard manifolds.
        SIAM Journal on Imaging Sciences. 9, (3), 901-937. ( )
        [doi] [www] 

      • F. Pierre, J.F. Aujol, A. Bugeau, G. Steidl, V. T. Ta, (2016).
        Hue-preserving perceptual contrast enhancement.
        Proc. International Conference on Image Processing (ICIP) 2016. 1-5.
        [pdf]

      • S. Dahlke, F. De Mari, E. De Vito, S. Häuser, G. Steidl, G. Teschke (2016).
        Different faces of the Shearlet group.
        The Journal of Geometric Analysis. 26, (3), 1693-1729.
        [pdf] [www] 

      • J. H. Fitschen, F. Laus and G. Steidl (2016).
        Transport between RGB images motivated by dynamic optimal transport.
        Journal of Mathematical Imaging and Vision. 56, (3), 409-429.
        [pdf] [www] 

      2015

      • S. Dahlke, S. Häuser, G. Steidl, G. Teschke (2015).
        Shearlet Coorbit spaces: Traces and embeddings in higher dimensions.
        Monatshefte für Mathematik. 169, (1), 15 - 32.
        [pdf] [doi] 

      • X. Cai, J. H. Fitschen, M. Nikolova, G. Steidl, M. Storath (2015).
        Disparity and optical flow partitioning using extended Potts priors.
        IMA Journal of Information and Inference. 4, (1), 43-62.
        [doi] [www] 

      • S. Dahlke, S. Häuser, G. Steidl, G. Teschke (2015).
        Shearlet coorbit theory.
        S. Dahlke, F. DeMari, P. Grohs, D. Labate (eds.)
        Harmonic and Applied Analysis
        . Birkhäuser: 83-147.  

      • Z. Mortezapouraghdam, L. Haab, F.I. Corona-Strauss, G. Steidl, D.J. Strauss (2015).
        Assessment of long-term habituation correlates in event-related potentials using a von Mises model.
        IEEE Transactions on Neural Systems & Rehabilitation Engineering. 363-373.
        [doi]

      • G. Moerkotte, M. Montag, A. Repetti, G. Steidl (2015).
        Proximal operator of quotient functions with application to a feasibility problem in query optimization.
        Journal of Computational and Applied Mathematics. 285, 243-255.
        [pdf]

      • J. Fehrenbach, M. Nikolova and G. Steidl, P. Weiss (2015).
        Bilevel image denoising using Gaussianity tests.
        Scale Space and Variational Methods in Computer Vision. Aujol, Jean-François and Nikolova, Mila and Papadakis, Nicolas (eds.) Lecture Notes in Computer Science 9087, 117-128.
        [doi] [www] 
      • F. Balle, D. Eifler, J. H. Fitschen, S. Schuff, G. Steidl (2015).
        Computation and visualization of local deformation for multiphase metallic materials by infimal convolution of TV-type functionals.
        Scale Space and Variational Methods in Computer Vision. Aujol, Jean-François and Nikolova, Mila and Papadakis, Nicolas (eds.) Lecture Notes in Computer Science 9087, 385-396.
        [doi] [www] 
      • J. H. Fitschen, M. Nikolova, F. Pierre, G. Steidl (2015).
        A variational model for color assignment.
        Scale Space and Variational Methods in Computer Vision. Aujol, Jean-François and Nikolova, Mila and Papadakis, Nicolas (eds.) Lecture Notes in Computer Science 9087, 437-448.
        [doi] [www] 
      • G. Steidl (2015).
        Combined first and second order variational approaches for image processing.
        Jahresbericht der Deutschen Mathematiker-Vereinigung 2015. 117, (2), 133-160.
        [pdf] 

      • J. H. Fitschen, F. Laus, G. Steidl (2015).
        Dynamic optimal transport with mixed boundary condition for color image processing.
        International Conference on Sampling Theory and Applications (SampTA), 2015. 558-562.
        [doi] [www] 

      2014

      • Schubert, Gonzalez-Trejo, Retz, Rösler, Corona-Strauss, Steidl, Teuber, Strauss (2014).
        Dysfunctional cortical inhibition in adult ADHD: Neural correlates in auditory event-related potentials.
        Journal of Neuroscience Methods. (235), 181-188. doi: 10.1016/j.jneumeth.2014.06.025. Epub 2014 Jul 14.
         

      • S. Häuser, B. Heise, G. Steidl (2014).
        Linearized Riesz transform and quasi-monogenic shearlets.
        International Journal of Wavelets, Multiresolution and Information Processing. 12, (3), 1450027-1 – 1450027-25.
        [pdf] [doi] [www] 

      • F. Baus and M. Nikolova, G. Steidl (2014).
        Smooth objectives composed of asymptotically affine data-fidelity and regularization: Bounds for the minimizers and parameter choice.
        Journal of Mathematical Imaging and Vision. 48, (2), 295-307.
        [www] 

      • A. Liebscher, J. Meinhardt, A. Rack, K. Schladitz, B. Shafei, G. Steidl, O. Wirjadi (2014).
        Microstructural analysis of a C/SiC ceramic based on the segmentation of 3D image data.
        International Journal of Materials Research. 105, (7), 702 - 708.
        [doi] [www] 

      • S. H. Kang , B. Shafei, G. Steidl (2014).
        Supervised and transductive multi-class segmentation using -Laplacians and RKHS methods.
        J. Visual Communication and Image Representation. 25, (5), 1136-1148.
        [pdf] 

      • M. Nikolova, G. Steidl (2014).
        Fast ordering algorithm for exact histogram specification.
        IEEE Transactions on Image Processing. 23, (12), 5274 - 5283. (for software see www)
        [pdf] [doi] [www] 

      • M. Nikolova, G. Steidl (2014).
        Fast hue and range preserving histogram specification: Theory and new algorithms for color image enhancement.
        IEEE Transactions on Image Processing. 23, (9), 4087-4100. (For SOFTWARE of the paper please click on the link at www below)
        [pdf] [www] 

      • R. Bergmann, F. Laus, G. Steidl, A. Weinmann (2014).
        Second order differences of cyclic data and applications in variational denoising.
        SIAM Journal on Imaging Sciences. 7, (4), 2916-2953.
        [pdf] 

      • G. Kutyniok, W. Lim, G. Steidl (2014).
        Shearlets: Theory and applications.
        GAMM-Mitteilungen. 1-2, (14), 259-280.
        [pdf] 

      2013

      • R. Ciak, B. Shafei, G. Steidl (2013).
        Homogeneous penalizers and constraints in convex image restoration.
        Journal of Mathematical Imaging and Vision. 47, (3), 210-230.
        [pdf] [doi] 

      • D. J. Strauss, T. Teuber, G. Steidl, F. I. Corona-Strauss (2013).
        Exploiting the self-similarity in ERP images by nonlocal means for single-trial denoising.
        IEEE Transactions on Neural Systems and Rehabilitation Engineering. 21, (4), 576-583.
        [doi]

      • S. Setzer, G. Steidl, J. Morgenthaler (2013).
        A cyclic projected gradient method.
        Computational Optimization and Applications. 54, (2), 417-440.
        [pdf]

      • S. Häuser, G. Steidl (2013).
        Convex multiclass segmentation with shearlet regularization.
        International Journal of Computer Mathematics. 90, (1), 62-81.
        [pdf] [doi] 

      • M. Fornasier, J. Haskovec, G. Steidl (2013).
        Consistency of variational continuous-domain quantization via kinetic theory.
        Applied Analysis. 92(6), 1283 - 1298.
        [pdf]

      • T. Teuber, G. Steidl, R. H. Chan (2013).
        Minimization and parameter estimation for seminorm regularization models with I-divergence constraints.
        Inverse Problems. 29, 1-28.
        [pdf] 

      • S. Harizanov, J.-C. Pesquet, G. Steidl (2013).
        Epigraphical projection for solving least squares Anscombe transformed constrained optimization problems.
        A. Kuijper et al., (eds.) Scale-Space and Variational Methods in Computer Vision. Lecture Notes in Computer Science, Vol. 7893. SSVM 2013, LNCS 7893 Springer-Verlag: Berlin 125-136.
        [www] 

      • X. Cai, G. Steidl (2013).
        Multiclass segmentation by iterated ROF thresholding.
        F. Kahl, A. Heyden, C. Olsson, M. Oskarsson, C.-C. Tai (eds.) Energy Minimization Methods in Computer Vision and Pattern Recognition. Lecture Notes in Computer Science. Springer: Berlin
        [pdf]

      2012

      • M. Gräf, D. Potts, G. Steidl (2012).
        Quadrature rules, discrepancies and their relations to halftoning on the torus and the sphere.
        SIAM Journal on Scientific Computing. 34/5, 2760-2791.
        [pdf] 

      • M. Gräf, D. Potts, G. Steidl (2012).
        Quadrature nodes meet stippling dots.
        A. M. Bruckstein, B. M. ter Haar Romney, A. M. Bronstein, M. M. Bronstein (eds.) Proceedings SSVM 2011. Springer: 568-580.
        [www]

      • T. Teuber, S. Remmele, J. Hesser, G. Steidl (2012).
        Denoising by second order statistics.
        Signal Processing. 92, (12), 2837-2847.
        [www] 

      • Y. He, B. Shafei, M. Y. Hussaini, J. Ma, G. Steidl (2012).
        A new fuzzy c-means method with total variation regularization for segmentation of images with noisy and incomplete data.
        Pattern Recognition. 45, 3436-3471.
        [www] 

      • S. Setzer, G. Steidl, T. Teuber (2012).
        On vector and matrix median computation.
        Journal of Computational and Applied Mathematics. 236, 2200-2222.
        [pdf] 

      • B. Shafei, G. Steidl (2012).
        Segmentation of images with separating layers by fuzzy c-means and convex optimization.
        J. Visual Communication and Image Representation. 23, 611-621.
        [pdf] 

      • S. Dahlke, G. Steidl, G. Teschke (2012).
        Multivariate shearlet transform, shearlet coorbit spaces and their structural properties.
        G. Kutyniok, D. Labate (eds.) Birkhäuser: 105-142.
        [pdf]

      2011

      • S. Dahlke, G. Steidl, G. Teschke (2011).
        Shearlet coorbit spaces: compactly supported analyzing shearlets, traces and embeddings.
        The Journal of Fourier Analysis and its Applications. 17, (6), 1232-1255.
        [pdf]

      • T. Teuber, G. Steidl, P. Gwosdek, C. Schmaltz, J. Weickert (2011).
        Dithering by differences of convex functions.
        SIAM Journal on Imaging Science. 4, (1), 79-108.
        [pdf]

      • S. Setzer, G. Steidl, T. Teuber (2011).
        Infimal convolution regularizations with discrete l1-type functionals.
        Communications in Mathematical Sciences. 9, (3), 797-872.
        [pdf]

      • G. Steidl (2011).
        Supervised learning by support vector machines.
        O. Scherzer (eds.) Handbook of Mathematical Methods in Imaging. Springer: 959-1014.
        [www]

      2010

      • S. Setzer, G. Steidl, T. Teuber (2010).
        Deblurring Poissonian images by split Bregman techniques.
        Journal of Visual Communication and Image Representation. 21, 193 - 199.
        [pdf] 

      • G. Steidl, T. Teuber (2010).
        Removing multiplicative noise by Douglas-Rachford splitting methods.
        Journal of Mathematical Imaging and Vision. 36, (2), 168-184.
        [pdf] 

      • S. Didas, G. Steidl, J. Weickert (2010).
        Integrodifferential equations for multiscale wavelet shrinkage: The discrete case.
        International Journal of Electrical and Computer Engineering Systems. 1, (1), 5-21.
        [pdf]

      • S. Setzer, G. Steidl, T. Teuber, G. Moerkotte (2010).
        Approximation related to quotient functionals.
        Journal of Approximation Theory. 162, (3), 545-558.
        [pdf] 

      • S. Dahlke, G. Steidl, G. Teschke (2010).
        The continuous shearlet transform in arbitrary dimensions.
        The Journal of Fourier Analysis and ist Applications. 16, (3), 340-464.
        [pdf] 

      2009

      • S. Didas, G. Steidl, S. Setzer (2009).
        Combined l_2 data and gradient fitting in conjunction with l_1 regularization.
        Advances in Computational Mathematics. 30, (1), 79-99.
        [pdf] 

      • S. Setzer, G. Steidl, B. Popilka, B. Burgeth (2009).
        Variational methods for denoising matrix fields.
        Visualization and Processing of Tensor Fields, Advances and Perspectives. D. H. Laidlaw and J. Weickert (eds.) Mathematics and Visualization 341-360.
        [www]

      • J. Yuan, C. Schnörr, G. Steidl (2009).
        Total-variation based piecewise affine regularization.
        A. Lie and M. Lysaker and K. Morken and X.-C. Tai (eds.) Second International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings. Springer: 552-564.
        [pdf]

      • G. Steidl, T. Teuber (2009).
        Anisotropic smoothing using double orientation.
        A. Lie and M. Lysaker and K. Morken and X.-C. Tai (eds.) Second International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2009, Voss, Norway, June 1-5, 2009. Proceedings. Springer: 477-489.
        [pdf]

      • J. Yuan, Ch. Schnörr, G. Steidl (2009).
        Convex Hodge decomposition and regularization of image flows.
        Journal of Mathematical Imaging and Vision. 33, (2), 169-177.
        [pdf]

      • S. Dahlke, G. Kutyniok, G. Steidl, G. Teschke (2009).
        Shearlet coorbit spaces and associated Banach frames.
        Applied and Computational Harmonic Analysis. 27, (2), 195-214.
        [www]

      • G. Steidl, T. Teuber (2009).
        Diffusion tensors for denoising sheared and rotated rectangles.
        IEEE Transactions on Image Processing. 18, (12), 2640-2648.
        [pdf]

      • G. Moerkotte, T. Neumann, G. Steidl (2009).
        Preventing bad plans by bounding the impact of cardinality estimation errors.
        Proc. of the VLDB. 2, (1), 982-993.
        [pdf] 

       2008

      • R. H. Chan, S. Setzer, G. Steidl (2008).
        Inpainting by flexible Haar-wavelet shrinkage.
        SIAM Journal on Imaging Science. 1, 273-293.
        [pdf] 

      • S. Dahlke, M. Fornasier, H. Rauhut, G. Steidl, G. Teschke (2008).
        Generalized coorbit theory, Banach frames and the relation to alpha-modulation spaces.
        Proc. London Mathematical Society. 6, (2), 464-506.
        [pdf] 

      • S. Setzer, G. Steidl (2008).
        Variational methods with higher order derivatives in image processing.
        M. Neamtu and L. L. Schumaker (eds.) Approximation XII, San Antonio, USA. Nashboro Press, Brentwood: 360-386.
        [pdf]

      • S. Setzer, G. Steidl, T. Teuber (2008).
        Restoration of images with rotated shapes.
        Numerical Algorithms. (48), 49-66.
        [pdf] 

      • M. Welk, G. Steidl, J. Weickert (2008).
        Locally analytic schemes: A link between diffusion filtering and wavelet shrinkage.
        Applied and Computational Harmonic Analysis. 24, 195-224.
        [pdf] 

      • R. Dahlhaus, J. Franke, J. Polzehl,  V. Spokoiny, G. Steidl, J. Weickert, A. Berdychevski, S. Didas, S. Halim, P. Mrazek, S. Subba Rao, J. Tadjuidje (2008).
        Structural adaptive smoothing procedures.
        R. Dahlhaus, J. Kurths, P. Maass, J. Timmer (eds.) Mathematical Methods for Time Series Analysis and Digital Image Processing. Springer: Berlin 183-229.
        [www]

      2007

      • S. Dahlke, G. Steidl, G. Teschke (2007).
        Frames and coorbit theory on homogeneous spaces with a special guidance on the sphere.
        The Journal of Fourier Analysis and Applications. 13, (4), 387-403.
        [doi]

      • G. Steidl, S. Setzer, B. Popilka, B. Burgeth (2007).
        Restoration of matrix fields by second order cone programming.
        Computing. 81, 161-178.
        [pdf]

      • B. Popilka, S. Setzer, G. Steidl (2007).
        Signal recovery from incomplete measurements in the presence of outliers.
        Inverse Problems and Imaging. 1, (4), 661-672.
        [pdf] 

      • J. Yuan, Ch. Schnörr, G. Steidl (2007).
        Simultaneous higher order optical flow estimation and decomposition.
        SIAM J. Sci. Comput.. 29, (6), 2283-2304.
        [pdf] 

      2006

      • M. Fenn, G. Steidl (2006).
        Robust local approximation of scattered data.
        Geometric Properties from Incomplete Data. R. Klette, R. Kozera, L. Noakes, J. Weickert (eds.) 317-334.
        [pdf]
      • S. Kunis, D. Potts, G. Steidl (2006).
        Fast Gauss transform with complex parameters.
        Journal of Numerical Mathematics. 14, (4), 247-318.
        [pdf] 

      • G. Plonka, G. Steidl (2006).
        A multiscale wavelet-inspired scheme for nonlinear diffusion.
        International Journal of Wavelets, Multiresolution and Information Processing. 4, (1), 1-21.
        [pdf]

      • G. Steidl (2006).
        A note on the dual treatment of higher order regularization functionals.
        Computing. 76, 135-148.
        [pdf] 

      • G. Steidl, S. Didas, J. Neumann (2006).
        Splines in higher order TV regularization.
        International Journal of Computer Vision. 70, 241-255.
        [pdf] 

      • M. Welk, J. Weickert, G. Steidl (2006).
        From tensor-driven diffusion to anisotropic wavelet shrinkage.
        Computer Vision - ECCV 2006. H. Bischof and A. Leonardis and A. Pinz (eds.) LNCS 3951, 391-403.
        [pdf] 

      2005

      • A. Kryvanos, J. Hesser, G. Steidl (2005).
        Nonlinear image restoration methods for marker extraction in 3D fluorescent microscopy.
        SPIE's 17th Annual Symposium EI05 - Electronic Imaging.
      • J. Neumann, C. Schnörr, G. Steidl (2005).
        Efficient wavelet adaption for Hybrid wavelet-large margin classifiers.
        Pattern Recognition. 38, (11), 1815-1830.
        [pdf] 

      • J. Neumann, C. Schnörr, G. Steidl (2005).
        Combined SVM-based feature selection and classification.
        Machine Learning. 61, 129-150.
        [pdf] 

      • J. Neumann, G. Steidl (2005).
        Dual-tree complex wavelet transform in the frequency domain and an application to signal classification.
        International Journal of Wavelets, Multiresolution and Information Processing. 3, (1), 43-66.
        [pdf] 

      • M. Welk, J. Weickert, G. Steidl (2005).
        A four-pixel scheme for singular differential equations.
        Scale-Space and PDE Methods in Computer Vision. R. Kimmel and N. Sochen and J. Weickert (eds.) 610-621.
        [pdf]
      • J. Yuan, Ch. Schnörr, G. Steidl, F. Becker (2005).
        A study of non-smooth convex flow decomposition.
        Proc. Variational, Geometric and Level Set Methods in Computer Vision. LNCS 3752, 1-12.
        [pdf] 
      • P. Mrazek, J. Weickert, G. Steidl (2005).
        Diffusion-inspired shrinkage functions and stability results for wavelet shrinkage.
        International Journal of Computer Vision. 64, (2/3), 171-186.
        [pdf] 

      • J. Weickert, G. Steidl, P. Mrazek, M. Welk, T. Brox (2005).
        Diffusion filters and wavelets: What can they learn from each other?.
        Handbook of Mathematical Models of Computer Vision. N. Paragios and Y. Chen and O. Faugeras (eds.) 3-16.
        [doi]
      • G. Steidl, S. Didas, J. Neumann (2005).
        Relations between higher order TV regularization and support vector regression.
        Scale-Space and PDE Methods in Computer Vision. R. Kimmel and N. Sochen and J. Weickert (eds.) LNCS 3459, 515-527.
        [pdf]

      2004

      • D. Potts, G. Steidl, A. Nieslony (2004).
        Fast convolution with radial kernels at nonequispaced knots.
        Numerische Mathematik. 98, (2), 329-351.
        [doi]

      • S. Dahlke, G. Steidl, G. Teschke (2004).
        Coorbit spaces and Banach frames on homogeneous spaces.
        Advances in Computational Mathematics. 21, 147-180.
        [pdf] 

      • S. Dahlke, G. Steidl, G. Teschke (2004).
        Weighted coorbit spaces and Banach frames on homogeneous spaces.
        The J. Fourier Anal. Appl. 10/5Advances in Computational Mathematics. 10, (5), 507-539.
        [pdf] 

      • M. Fenn, G. Steidl (2004).
        Fast NFFT based summation of radial functions.
        Sampling Theory in Signal and Image Processing. 3, (1), 1-28.
        [pdf] 

      • G. Steidl, J. Weickert, T. Brox, P. Mrázek, M. Welk (2004).
        On the equivalence of soft wavelet shrinkage, total variation diffusion, total variation regularization, and SIDEs.
        SIAM Journal on Numerical Analysis. 42, (2), 686-713.
        [pdf] 

      • D. J. Strauss, G. Steidl, U. Welzel (2004).
        Parameter detection of thin films from their X-ray reflectivity by support vector machines.
        Applied Numerical Mathematics. 48, 223-236.
        [pdf] 

      • J. Neumann, C. Schnörr, Steidl (2004).
        SVM-based feature selection by direct objective minimisation.
        Pattern Recognition. C. E. Rasmussen and H. H. Bülthoff, M. A. Giese and B. Schölkopf (eds.) LNCS 3175, 212-219.
        [pdf] 

      2003

      • T. Brox, M. Welk, G. Steidl, J. Weickert (2003).
        Equivalence results for TV diffusion and TV regularisation.
        L. D. Griffin and M. Lillholm (eds.) Scale-Space Methods in Computer Vision. Springer: Berlin 86-100.
        [pdf]
         

      • P. Mrázek, J. Weickert, G. Steidl (2003).
        Correspondences between wavelet shrinkage and nonlinear diffusion.
        L. D. Griffin and M. Lillholm (eds.) Scale-Space Methods in Computer Vision. Springer: Berlin 101-116.
        [www]

      • P. Mrázek, J. Weickert, G. Steidl, M. Welk (2003).
        On iterations and scales of nonlinear filters.
        O. Drbohlav (eds.) Proc. Eighth Computer Vision Winter Workshop. Czech Pattern Recognition Society: Valtice, Czech Republic 61-66.
        [pdf]

      • A. Nieslony, G. Steidl (2003).
        Sparse approximate factorization of nonuniform Fourier matrices.
        Linear Algebra and its Applications. 366, 337-351.
        [www]

      • G. Nürnberger, G. Steidl, F. Zeilfelder (2003).
        Explicit estimates for bivariate hierarchical bases.
        Communications in Applied Analysis. 7, (1), 133-151.
        [pdf]

      • D. Potts, G. Steidl (2003).
        Fast summation at nonequispaced knots by NFFTs.
        SIAM Journal on Scientific Computing. 24, 2013-2037.
        [pdf]

      • D. Strauss, G. Steidl, W. Delb (2003).
        Feature extraction by shape-adapted local discriminant bases.
        Signal Processing 83. 83, 359-376.
        [www]

      • J. Neumann, C. Schnörr, G. Steidl (2003).
        Feasible adaptation criteria for hybrid wavelet - large margin classifiers.
        N. Petkov and M. A. Westenberg (eds.) Computer Analysis of Images and Patterns.
        Springer: Berlin 588-599.
        [www]

      2002

      • M. Fenn, G. Steidl (2002).
        FMM and H-matrices: a short introduction to the basic idea,.
        Preprint, Univ. Mannheim.
         

      • D. Potts, G. Steidl, (2002).
        Rapid evaluation of radial functions by Fast Fast Fourier transform at nonequispaced knots: a users guide to a C-library, (software guide),.
        Preprint Univ. Lübeck.
         

      • D. Potts, G. Steidl, M. Tasche (2002).
        Numerical stability of fast trigonometric transforms - a worst case study.
        Journal of Concrete and Applied Mathematics. 1, 1-36.
        [www]

      • M. Fenn, G. Steidl (2002).
        FMM and H-matrices: a short introduction to the basic idea (teaching material).
        Preprint Univ. Mannheim.
        [pdf] 

      • G. Steidl, J. Weickert (2002).
        Relations between soft wavelet shrinkage and total variation denoising.
        Pattern Recognition. L. Van Gool (eds.) LNCS 2449, 198--205.

      • D. Potts, G. Steidl (2002).
        Rapid evaluation of radial functions by Fast Fast Fourier transform at nonequispaced knots: a users guide to a C-library.
        Software Guide, Preprint Univ. Lübeck.
         

      • D. Potts, G. Steidl (2002).
        Fourier reconstruction of functions from their nonstandard sampled Radon transform.
        The Journal of Fourier Analysis and its Applications. 8, 513-533.
        [pdf] 

      • D. Strauss, G. Steidl (2002).
        Hybrid wavelet-support vector classifiers of waveforms.
        Journal of Computational and Applied Mathematics. 148, 375-400.
        [pdf] 

      2001

      • D. Potts, G. Steidl, M. Tasche (2001).
        Fast Fourier transforms for nonequispaced data: A tutorial.
        Benedetto, John. J. and Ferreira, Paulo J. S. G. (eds.) Modern Sampling Theory: Mathematics and Applications. Birkhäuser: Boston 247-270.
        [pdf] 

      • R. H. Chan, D. Potts,G. Steidl (2001).
        Preconditioners for non-Hermitian Toeplitz systems.
        Numerical Linear Algebra and Applications. 8, (2), 83-98.
        [www] 

      • D. Potts, G. Steidl (2001).
        A new linogram algorithm for computerized tomography.
        IMA Journal on Numerical Analysis. 21, 769-782.
        [pdf] 

      • D. Potts, G. Steidl (2001).
        Preconditioners for ill-conditioned Toeplitz matrices constructed from positive kernels.
        SIAM Journal on Scientific Computing. 22, (5), 1741-1761.
        [pdf] 

      • D. Potts, G. Steidl (2001).
        Preconditioning of Hermitian block-Toeplitz-Toeplitz-block matrices by level-1 preconditioners.
        V. Olshevsky (eds.) Structured Matrices in Mathematics, Computer Science, and Engineering II. AMS: Providence 193-212.
        [pdf] 

      • D. Strauss, G. Steidl, J. Jung (2001).
        Arrhythmia detection using signal adapted wavelet preprocessing for support vector machines.
        IEEE Computers in Cardiology. 28, 497-501.
        [www]

      2000

      •  B. Trebels, G. Steidl (2000).
        Riesz bounds of Wilson bases generated by B-splines.

        The Journal of Fourier Analysis and its Applications. 6, (2), 159-172.
        [www]

      • R. H. Chan, D. Potts, G. Steidl (2000).
        Preconditioners for nondefinite Hermitian Toeplitz systems.
        SIAM Journal on Matrix Analysis and Applications. 22, 647-665.
        [pdf] 

      • D. Potts, G. Steidl (2000).
        New Fourier reconstruction algorithms for computerized tomography.
        A. Aldroubi and A. F. Laine and M. A. Unser (eds.) Wavelet Applications in Signal and Iamge Processing VIII. San Diego 13-23.
        [www]

       

       

      • A. Gottscheber, G. Steidl (1999).
        On a family of orthogonal wavelets on the quincunx grid.
        In: Advances in Multivariate Approximation. W. Haussmann, K. Jetter and M. Reimer: Wiley-VCH, Berlin 175 - 184.
        [pdf] 

      • D. Potts, G. Steidl (1999).
        Preconditioners for ill-conditioned Toeplitz matrices.
        BIT. 39/3, 513 - 533.
        [www]
      • D. Potts, G. Steidl, M. Tasche (1998).
        Fast and stable algorithms for discrete spherical Fourier transforms.
        Linear Algebra Appl.. 275 - 276, 433 - 450.
        [pdf]

      • D. Potts, G. Steidl (1998).
        Optimal trigonometric preconditioners for nonsymmetric Toeplitz systems.
        Linear Algebra Appl.. 281, 265 - 292.
        [www]

      • D. Potts, G. Steidl, M. Tasche (1998).
        Fast algorithms for discrete polynomial transforms.
        Math. Comp.. 67, 1577 - 1590.
        [www]

      • G. Steidl (1998).
        A note on fast Fourier transforms for nonequispaced grids.
        Adv. Comput. Math.. 9, 337 - 353.
        [www]

      • G. Steidl, M. Tasche (1998).
        Elemente der Fourier-Analysis.
        In: Lehrbriefe Fernuniversität Hagen.

      • A. Elbel, G. Steidl (1998).
        Fast Fourier transforms for nonequispaced data.
        C.K. Chui and L.L. Schumaker (eds.) In: Approximation Theory IX,.
        Vanderbuilt University Press, 39 -46.
         

      • D. Potts, G. Steidl, M. Tasche (1997).
        Trigonometric preconditioners for block Toeplitz systems.
        In: Multivariate Approximation and Splines. G. Nürnberger, J. W. Schmidt and G. Walz: Birkhäuser- Verlag Basel, 219 - 234.
        [www]

      • D. Potts, G. Steidl, M. Tasche (1996).
        Kernels of spherical harmonics and spherical frames.
        F. Fontanella, K. Jetter and P. J. Laurent, (eds.) In: Advanced Topics in Multivariate Approximation. World Scientific Publishing Co., Verlag Basel 287 - 301.
        [pdf] 

      • M. Konik, R. Schneider, G. Steidl (1995).
        Matrix sparsification by discrete multiscale methods.
        C.K. Chui and L.L. Schumaker, (eds.) In: Approximation and Decomposition.
        World Scientific Publishing Co. 225 - 234.
         

      • B. Glaser, M. Konik, G. Steidl, (1995).
        Multiskalenanalyse des Ankerstroms eines permanetmagneterregten Gleichstrommotors.
        In: Proc. Internat. Conf. on Wavelet-Approximation and Applications. Lübeck
         

      • G. Steidl (1995).
        On multivariate attenuation factors.
        Numer. Algorithms. 9, 245 - 261.
         

      • G. Steidl (1994).
        Wavelets over R, Z, R/NZ and Z/NZ.
        C. K. Chui, L. Montefusco and L. Puccio (eds.) In: Wavelets: Theory, Algorithms and Applications. Academic Press 155 - 179.
        [www]

      • G. Steidl (1992).
        Fast radix-p discrete cosine transform.
        Appl. Algebra Engrg. Comm. Comput.. 3, 39 - 46.
        [www]

      • G. Steidl (1992).
        Chebyshev polynomial derivation of composite-length DCT algorithms.
        Signal Processing. 29, 17 - 27.
        [www] 

      • G. Steidl, M. Tasche (1991).
        Polynomial approach to fast algorithms for discrete Fourier-cosine- and Fourier-sine-transforms.
        Math. Comp.. 56, 282 - 296.
        [www] 

      • G. Steidl, M. Tasche, R. Creutzburg (1991).
        Number-theoretic transforms and a theorem of Sylvester-Kronecker-Zsygmondy.
        A. Pethö, M. Pohst, H. C. Williams und H. G. Zimmer (eds.) Computational Number Theory. de Gruyter Berlin - New York 45 - 50.
         

      • G. Steidl (1990).
        On normal bases for finite commutative rings.
        Math. Nachr.. 145, 131 - 148.
         

      • G. Steidl (1990).
        Generalization of the algebraic discrete Fourier transform with application to fast convolutions.
        Linear Algebra Appl.. 139, 181 - 206.
        [www]
         

      • G. Steidl (1990).
        Existence and construction of self-complementary normal bases.
        J. Inf. Process. Cybern.. EIK-26, 643 - 651.
         

      • G. Steidl, M. Tasche (1990).
        Fast algorithms for one-and twodimensional discrete cosine transforms.
        W. Haussmann und K. Jetter, (eds.) In: Multivariate Approximation and Interpolation. ISNM 94, Birkhäuser - Verlag Basel, 285 - 298.
        [www] 

      • G. Steidl, M. Tasche, (1989).
        On a number-theoretic result of Kronecker-Sylvester-Zsigmondy.
        Math. Nachr.. 140, 233 - 247.
        [www]

      • G. Steidl, M. Hänler, M. Tasche, (1989).
        On a number-theoretic result of Zsigmondy in domains of quadratic integers.
        Arch. Math.. 53, 30 - 39.
        [www] 

      • G. Steidl, M. Tasche, (1989).
        Index transforms for multidimensional discrete Fourier transforms.
        C. K. Chui, W. Schempp und K. Zeller (Eds.), ISNM 90 (eds.) In: Multivariate Approximation Theory IV. Birkhäuser - Verlag Basel 321 - 328.
        [www] 

      • G. Steidl, M. Tasche (1989).
        Index transforms for multidimensional DFT's and convolutions.
        Numer. Math.. 56, 513 - 528.
        [www] 

      • G. Steidl (1989).
        On symmetric radix-representation of Gaussian integers.
        BIT. 29, 563 - 571.
        [pdf] 

      • G. Steidl, M. Tasche (1988).
        Exact deconvolution using number-theoretic transforms.
        Comput. Math. Appl.. 15, 757 - 768.
        [www] 

      • G. Steidl, R. Creutzburg, (1988).
        Number-theoretic transforms in rings of cyclotomic integers.
        J. Inf. Process. Cybern.. EIK-24, 573 - 584.
         

      • G. Steidl (1988).
        Algebraic discrete Fourier transforms and fast convolution algorithms.
        Proc. IMYCS'88, Smolenice: 219 - 225.
         

      • G. Steidl, M. Tasche (1987).
        Prime factorization for values of cyclotomic polynomials in Z [i].
        Arch. Math.. 49, 292 - 300.

      Curriculum Vitae

      Gabriele Steidl received her PhD and Habilitation in Mathematics from the University of Rostock (Germany), in 1988 and 1991, respectively.

      From 1992 to 1993 she worked as a consultant at the Verband Deutscher Rentenversicherungsträger in Frankfurt am Main.
      From 1993 to 1996, she held a position as Assistant Professor at the Department of Mathematics at the TU Darmstadt.
      From 1996 to 2010, she was Professor at the Department of Mathematics and Computer Science at the University of Mannheim.

      Since 2011, she is Professor at the Department of Mathematics at the TU Kaiserslautern and Consultant of the Fraunhofer Institute for Industrial Mathematics.

      She worked as a Postdoc at the University of Debrecen (Hungary), the Banach Center Warsaw and the University of Zürich and was a Visiting Professor at the ENS Paris/Cachan and the Université Paris East Marne-la-Vallée and the Sorbonne.

      She is a member of the Editorial board of Journal of Mathematical Imaging and Vision, SIAM Journal on Imaging Sciences, The Journal of Fourier Analysis, Inverse Problems and Imaging, Transactions in Mathematics and its Applications and Acta Applicandae Mathematicae (ACAP).

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