Abstract
Image reconstruction from a fiducial collection of scale space interest points and attributes (e.g. in terms of image derivatives) can be used to make the amount of information contained in them explicit. Previous work by various authors includes both linear and non-linear image reconstruction schemes. In this paper, the authors present new results on image reconstruction using a top point representation of an image. A hierarchical ordering of top points based on a stability measure is presented, comparable to feature strength presented in various other works. By taking this into account our results show improved reconstructions from top points compared to previous work. The proposed top point representation is compared with previously proposed representations based on alternative feature sets, such as blobs using two reconstruction schemes (one linear, one non-linear). The stability of the reconstruction from the proposed top point representation under noise is also considered.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Brox, T., Weickert, J.: A tv flow based local scale measure for texture discrimination. In: Pajdla, T., Matas, J(G.) (eds.) ECCV 2004. LNCS, vol. 3022, pp. 578–590. Springer, Heidelberg (2004)
Janssen, B.J., Kanters, F.M.W., Duits, R., Florack, L.M.J.: A linear image reconstruction framework based on Sobolev type inner products. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds.) Scale-Space 2005. LNCS, vol. 3459, pp. 85–96. Springer, Heidelberg (2005)
Kanters, F.M.W., Platel, B., Florack, L.M.J., ter Haar Romeny, B.M.: Image reconstruction from multiscale critical points. In: Griffin, L.D., Lillholm, M. (eds.) Scale-Space 2003. LNCS, vol. 2695, pp. 464–478. Springer, Heidelberg (2003)
Kuijper, A., Florack, L.M.J.: Hierarchical pre-segmentation without prior knowledge. In: Proceedings of the 8th International Conference on Computer Vision, Vancouver, Canada, July 9–12, pp. 487–493. IEEE Computer Society Press, Los Alamitos (2001)
Lillholm, M., Nielsen, M., Griffin, L.D.: Feature-based image analysis. International Journal of Computer Vision 52(2/3), 73–95 (2003)
Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30(2), 79–116 (1998)
Nielsen, M., Lillholm, M.: What do features tell about images? In: Kerckhove, M. (ed.) Scale-Space 2001. LNCS, vol. 2106, pp. 39–50. Springer, Heidelberg (2001)
Platel, B., Kanters, F.M.W., Florack, L.M.J., Balmachnova, E.G.: Using multiscale top points in image matching. In: Proceedings of the 11th international conference on Image Processing, Singapore (October 2004)
Tikhonov, A., Arseninn, V.Y.: Solution of Ill-Posed Problems. John Wiley & Sons, New York (1977)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kanters, F. et al. (2005). On Image Reconstruction from Multiscale Top Points. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds) Scale Space and PDE Methods in Computer Vision. Scale-Space 2005. Lecture Notes in Computer Science, vol 3459. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408031_37
Download citation
DOI: https://doi.org/10.1007/11408031_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25547-5
Online ISBN: 978-3-540-32012-8
eBook Packages: Computer ScienceComputer Science (R0)