Abstract
In this paper we propose a novel type of scales-spaces which is emerging from the family of inhomogeneous pseudodifferential equations \((I - \tau\Delta)^{\frac{t}{2}}u\) with τ ≥ 0 and scale parameter t ≥ 0. Since they are connected to the convolution semi-group of Bessel potentials we call the associated operators {R \(^{n}_{t,{ \tau}}\) | 0≤ τ,t} either Bessel scale-space (τ=1), R \(^{n}_{t}\) for short, or scaled Bessel scale-space (τ ≠1). This is the first concrete example of a family of scale-spaces that is not originating from a PDE of parabolic type and where the Fourier transforms \(\mathcal{F}(R^n_{t,\tau})\) do not have exponential form. These properties make them different from other scale-spaces considered so far in the literature in this field.
In contrast to the α-scale-spaces the integral kernels for R \(^{n}_{t,{\tau}}\) can be given in explicit form for any t, τ ≥ 0 involving the modified Bessel functions of third kind K ν . In theoretical investigations and numerical experiments on 1D and 2D data we compare this new scale-space with the classical Gaussian one.
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References
Abramowitz, M., Stegun, I.A. (eds.): Handbook of Mathematical Functions, 9th edn. Dover Publications, Inc., New York (1972)
Alvarez, L., Guichard, F., Lions, P.-L., Morel, J.-M.: Axioms and fundamental equations in image processing. Archive for Rational Mechanics and Analysis 123, 199–257 (1993)
Aubert, G., Kornprobst, P.: Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations. Applied Mathematical Sciences, vol. 147. Springer, New York (2002)
Babaud, J., Witkin, A.P., Baudin, M., Duda, R.O.: Uniqueness of the Gaussian kernel for scale space filtering. IEEE Transactions on Pattern Analysis and Machine Intelligence 8, 26–33 (1986)
Bauer, H.: Wahrscheinlichkeitstheorie. Walter de Gruyter, Berlin (1991)
Brockett, R.W., Maragos, P.: Evolution equations for continuous-scale morphological filtering. IEEE Transactions on Signal Processing 42, 3377–3386 (1994)
Burgeth, B., Didas, S., Weickert, J.: Relativistic scale-spaces. In: Kimmel, R., Sochen, N.A., Weickert, J. (eds.) Scale-Space 2005. LNCS, vol. 3459, pp. 1–12. Springer, Heidelberg (2005)
Cao, F.: Geometric Curve Evolution and Image Processing. Lecture Notes in Mathematics, vol. 1805. Springer, Berlin (2003)
Donoghue, W.F.: Distributions and Fourier Tarnsforms. Academic Press, New York (1969)
Duits, R., Florack, L., de Graaf, J., ter Haar Romeny, B.: On the axioms of scale space theory. JMIV 20(3), 267–298 (2004)
Felsberg, M., Sommer, G.: Scale-adaptive filtering derived from the Laplace equation. In: Radig, B., Florczyk, S. (eds.) Dagstuhl Seminar 2000. LNCS, vol. 2032, pp. 95–106. Springer, Berlin (2001)
Florack, L.: Image Structure. Computational Imaging and Vision, vol. 10. Kluwer, Dordrecht (1997)
Gilboa, G., Sochen, N.A., Zeevi, Y.Y.: Forward-and-backward diffusion processes for adaptive image enhancement and denoising. IEEE Transactions on Image Processing 11(7), 689–703 (2002)
Hao, P., Zhang, C., Dang, A.: Co-histogram and image degradation evaluation. In: Campilho, A.C., Kamel, M.S. (eds.) ICIAR 2004. LNCS, vol. 3211, pp. 195–203. Springer, Heidelberg (2004)
Heijmans, H.J.A.M.: Scale-spaces, PDEs and scale-invariance. In: Kerckhove, M. (ed.) Scale-Space 2001. LNCS, vol. 2106, pp. 215–226. Springer, Heidelberg (2001)
Hille, E., Philips, R.S.: Functional Analysis and Semi-Groups. American Mathematical Society, Providence (1957)
Iijima, T.: Basic theory of pattern observation. Papers of Technical Group on Automata and Automatic Control. IECE, Japan (December 1959) (In Japanese)
Iijima, T.: Basic theory on the construction of figure space. Systems, Computers, Controls 2(5), 51–57 (1971) (In English)
Jackway, P.T., Deriche, M.: Scale-space properties of the multiscale morphological dilation–erosion. IEEE Transactions on Pattern Analysis and Machine Intelligence 18, 38–51 (1996)
Kimmel, R.: Numerical Geometry of Images: Theory, Algorithms, and Applications. Springer, New York (2003)
Lindeberg, T.: Scale-Space Theory in Computer Vision. Kluwer, Boston (1994)
Lindeberg, T.: On the axiomatic formulations of linear scale-space. In: Sporring, J., Nielsen, M., Florack, L., Johansen, P. (eds.) Gaussian Scale-Space Theory. Computational Imaging and Vision, vol. 8, pp. 75–97. Kluwer, Dordrecht (1997)
Aronszajn, N., Smith, K.T.: Theory of bessel potentials. Ann. Inst. Fourier (Grenoble) 11, 385–475 (1961)
Olver, P.J., Sapiro, G., Tannenbaum, A.: Classification and uniqueness of invariant geometric flows. Comptes Rendus de l’Académie des Sciences de Paris, Série I 319, 339–344 (1994)
Pauwels, E.J., Van Gool, L.J., Fiddelaers, P., Moons, T.: An extended class of scale-invariant and recursive scale space filters. IEEE Transactions on Pattern Analysis and Machine Intelligence 17, 691–701 (1995)
Perona, P., Malik, J.: Scale space and edge detection using anisotropic diffusion. IEEE Transactions on Pattern Analysis and Machine Intelligence 12, 629–639 (1990)
Salden, A.H.: Dynamic Scale-Space Paradigms. PhD thesis, Faculty of Medicine, Utrecht University, The Netherlands (November 1996)
Sapiro, G., Tannenbaum, A.: Affine invariant scale-space. International Journal of Computer Vision 11, 25–44 (1993)
Sporring, J., Nielsen, M., Florack, L., Johansen, P. (eds.): Gaussian Scale-Space Theory. Computational Imaging and Vision, vol. 8. Kluwer, Dordrecht (1997)
Taylor, M.E.: Partial Differential Equations I – Basic Theory. Springer, New York (1996)
ter Haar Romeny, B.M. (ed.): Geometry-Driven Diffusion in Computer Vision. Computational Imaging and Vision, vol. 1. Kluwer, Dordrecht (1994)
van den Boomgaard, R.: The morphological equivalent of the Gauss convolution. Nieuw Archief Voor Wiskunde 10(3), 219–236 (1992)
Weickert, J.: Anisotropic Diffusion in Image Processing. Teubner, Stuttgart (1998)
Weickert, J., Ishikawa, S., Imiya, A.: Linear scale-space has first been proposed in Japan. Journal of Mathematical Imaging and Vision 10(3), 237–252 (1999)
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Burgeth, B., Didas, S., Weickert, J. (2005). The Bessel Scale-Space. In: Fogh Olsen, O., Florack, L., Kuijper, A. (eds) Deep Structure, Singularities, and Computer Vision. DSSCV 2005. Lecture Notes in Computer Science, vol 3753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11577812_8
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DOI: https://doi.org/10.1007/11577812_8
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