Acar, R. and Vogel, C.R., Analysis of bounded variation penalty methods for ill-posed problems, Inverse Problems, 10(6), pp. 1217–1229, 1994.
Bai, Z.-Z., Huang, Y.-M. and Ng, M.K., On preconditioned iterative methods for Burgers equations, SIAM Journal on Scientific Computing, 29(1), pp. 415–439, 2007.
Bai, Z.-Z., Huang, Y.-M. and Ng, M.K., On preconditioned iterative methods for certain time-dependent partial differential equations, SIAM Journal on Numerical Analysis, 47(2), pp. 1019–1037, 2009.
Bai, Z.-Z. and Ng, M.K., On inexact preconditioners for nonsymmetric matrices, SIAM Journal on Scientific Computing, 26(5), pp. 1710–1724, 2005.
Bai, Z.-Z., Ng, M.K. and Wang, Z.-Q., Constraint preconditioners for symmetric indefinite matrices, SIAM Journal on Matrix Analysis and Applications, 31(2), pp. 410–433, 2009.
Brown, L.G., A survey of image registration techniques, ACM Computing Surveys, 24(4), pp. 325–376, 1992.
Chan, T.F., Chen, K. and Carter, J.L., Iterative methods for solving the dual formulation arising fromimage restoration, Electronic Transactions on Numerical Analysis, 26, pp. 299–311, 2007.
Chan, T.F. and Shen, J.-H., Image Processing and Analysis-Variational, PDE, Wavelet, and Stochastic Methods, SIAM, Philadelphia, 2005.
Chen, H.-M., Arora, M.K. and Varshney, P.K., Mutual information based image registration for remote sensing data, International Journal of Remote Sensing, 24(18), pp. 3701–3706, 2003.
Chen, K., Matrix Preconditioning Techniques and Applications, Cambridge University Press, UK, 2005.
Chen, K. and Tai, X.-C., A nonlinear multigrid method for total variation minimization from image restoration, Journal of Scientific Computing, 32(2), pp. 115–138, 2007.
Chumchob, N. and Chen, K., A robust multigrid approach for variational image registration models, Journal of Computational and Applied Mathematics, 236(5), pp. 653–674, 2011.
Chumchob, N., Chen, K. and Brito-Loeza, C., A fourth order variational image registration model and its fast multigrid algorithm, Multiscale Modeling and Simulation, 9(1), pp. 89–128, 2011.
Fischer, B. and Modersitzki, J., Curvature based image registration, Journal of Mathematical Imaging and Vision, 18(1), pp. 81–85, 2003.
Frohn-Schauf, C., Henn, S., Hömke, L. and Witsch, K., Total variation based image registration, in Proceedings of the International Conference on PDE-Based Image Processing and Related Inverse Problems Series: Mathematics and Visualization, Springer-Verlag, pp. 305–323, 2006.
Frohn-Schauf, C., Henn, S. and Witsch, K., Multigrid based total variation image registration, Computing and Visualization in Science, 11(2), pp. 101–113, 2008.
Gill, P.E., Murray, W. and Wright, M.H., Practical Optimization, Academic Press, London, 1981.
Gratton, S., Lawless, A.S. and Nichols, N.K., Approximate Gauss-Newton methods for nonlinear least squares problems, SIAM Journal on Optimization, 18(1), pp. 106–132, 2007.
Haber, E., Heldmann, S. and Modersitzki, J., Adaptive mesh refinement for non parametric image registration, SIAM Journal on Scientific Computing, 30(6), pp. 3012–3027, 2008.
Haber, E., Heldmann, S. and Modersitzki, J., A computational framework for image-based constrained registration, Linear Algebra and its Applications, 431(3–4), pp. 459–470, 2009.
Haber, E., Horesh, R. and Modersitzki, J., Numerical optimization for constrained image registration, Numerical Linear Algebra with Applications, 17(2-3), pp. 343–359, 2010.
Haber, E. and Modersitzki, J., Numerical methods for volume preserving image registration, Inverse Problems, 20, pp. 1621–1638, 2004.
Haber, E. and Modersitzki, J., A multilevel method for image registration, SIAM Journal on Scientific Computing, 27(5), pp. 1594–1607, 2006.
Hajnal, J.V., Hawkes, D.J. and Hill, D.L.G., Medical Image Registration, The Biomedical Engineering Series, CRC Press, 2001.
Henn, S., A multigrid method for a fourth-order diffusion equation with application to image processing, SIAM Journal on Scientific Computing, 27(3), pp. 831–849, 2005.
Köstler, H., Ruhnau, K. and Wienands, R., Multigrid solution of the optical flow system using a combined diffusion- and curvature-based regularizer, Numerical Linear Algebra with Applications, 15(2-3), pp. 201–218, 2008.
Maintz, J.B.A. and Viergever, M.A., A survey of medical image registration, Medical Image Analysis, 2(1), pp. 1–36, 1998.
Modersitzki, J., Numerical Methods for Image Registration, Oxford University Press, New York, 2004.
Modersitzki, J., FAIR: Flexible Algorithms for Image Registration, SIAM, Philadelphia, 2009.
Nocedal, J. and Wright, S.J., Numerical Optimization, Springer-Verlag, New York, 1999.
Rudin, L., Osher, S. and Fatemi, E., Nonlinear total variation based noise removal algorithms, Physica D: Nonlinear Phenomena, 60(1-4), pp. 259–268, 1992.
Savage, J. and Chen, K., An improved and accelerated nonlinear multigrid method for total-variation denoising, International Journal of Computer Mathematics, 82(8), pp. 1001–1015, 2005.
Sorzano, C., Thévenaz, P. and Unser, M., Elastic registration of biological, images using vector-spline regularization, IEEE Transactions On Biomedical Engineering, 52(4), pp. 652–663, 2005.
Stürmer, M., Köstler, H. and Rüde, U., A fast full mulitigrid solver for applications in image processing, Numerical Linear Algebra with Applications, 15(2-3), pp. 187–200, 2008.
Thévenaz, P. and Unser, M., Optimization of mutual information for multiresolution image registration, IEEE Transactions on Image Processing, 9(12), pp. 2083–2099, 2000.
Vogel, C.R., Computational Methods for Inverse Problems, SIAM, Philadelphia, 2002.
Vogel, C.R. and Oman, M.E., Iterative methods for total variation denoising, SIAM Journal on Scientific Computing, 17(1), pp. 227–238, 1996.