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Methoden der Digitalen Signalverarbeitung in der Bildverarbeitung und Mustererkennung

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Mustererkennung 1986

Part of the book series: Informatik-Fachberichte ((2252,volume 125))

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Kurzfassung

Die eindimensionale digitale Signalverarbeitung und Systemtheorie war schon immer Quelle vieler Anregungen fur die digitale Bildverarbeitung und Mustererkennung. In der vorliegenden Übersicht werden neuere Beispiele für den Methodentransfer aufgezeigt. Die Ausführungen erheben keinen Anspruch auf Vollständigkeit, sie sollen vielmehr als exemplarische Anregungen verstanden werden.

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Literatur

  1. C.W. Themen, T.F. Quatieri, D.E. Dudgeon: Statistical Model-Based Algorithms for Image Analysis. Proc. of the IEEE, Vol. 74, April 1986, S. 532–551.

    Article  Google Scholar 

  2. A.K. Jain: Advances in Mathematical Models for Image Processing. Proc. of the IEEE, Vol. 69, Mai 1981, S. 502–528.

    Article  Google Scholar 

  3. D.E. Dudgeon, R.M. Mersereau: Multidimensional Digital Signal Processing. Prentice-Hall, 1984.

    Google Scholar 

  4. S.M. Kay, S.L. Marple: Spectrum Analysis — A Modern Perspective. Proc. of the IEEE, Vol. 69, Nov. 1981, S. 1380–1419.

    Article  Google Scholar 

  5. H.G, Musmann, P. Pirsch, H.-J, Grallert: Advances in Picture Coding. Proc. of the IEEE, Vol. 73, Apr. 1985, S. 523–530.

    Article  Google Scholar 

  6. W.K. Pratt: Digital Image Processing. John Wiley, 1978.

    Google Scholar 

  7. Burkhardt H., Diehl N.: Simultaneous Estimation of Rotation and Translation in Image Sequences. Proc. of the European Signal Processing Conference, EUSIPCO-86, Den Haag, Sept. 86.

    Google Scholar 

  8. Diehl N., Burkhardt H.: Planar Motion Estimation with a Fast Converging Algorithm. Proc. of the 8th Intern. Conf. on Pattern Recognition, Paris, Okt. 86.

    Google Scholar 

  9. R. Chellappa, S. Chatterjee: Classification of Textures Using Gaussian Markov Random Fields. IEEE Trans, on Acoustics, Speech, and Signal Processing, Vol. ASSP-33, Aug. 1985, S. 959–963.

    Article  MathSciNet  Google Scholar 

  10. R. Chellappa, R.L. Kashyap: Texture Synthesis Using 2-D Noncausal Autoregressive Models. IEEE Trans, on Acoustics, Speech, and Sipal Processing, Vol. ASSP-33, Febr. 1985, S. 194–203.

    Article  Google Scholar 

  11. Persoon E., Fu K.S.: Shape Discrimination Using Fourier Descriptors. IEEE Trans, on Systems, Man, and Cybernetics, Vol. SMC-7, März 1977, S. 170–179.

    Article  MathSciNet  Google Scholar 

  12. Burkhardt H.: Transformationen zur lageinvarianten Merkmalgewinnung. Habilitationsschrift, Universität Karlsruhe. Ersch. als Fortschrittbericht (Reihe 10, Nr. 7) der VDI-Zeitschriften, VDI-Verlag, 1979.

    Google Scholar 

  13. Arbter K.: Affininvariante Fourierdeskriptoren. Interner Bericht. Deutsche Versuchsanstalt für Luft-und Raumfahrt e.V., Institut für Dynamik der Flugsysteme, 1986.

    Google Scholar 

  14. R.E. Bellman, S.E. Dreyfus: Applied Dynamic Programming. Princeton University Press, 1962.

    Google Scholar 

  15. A.J. Viterbi: Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm. IEEE Trans, on Information Theory, Vol IT-13, Apr. 1967, S. 260–269.

    Article  Google Scholar 

  16. G.D. Forney: The Viterbi Algorithm. Proc of the IEEE, Vol. 61, März 1973, S. 268–278.

    Article  MathSciNet  Google Scholar 

  17. J.G. Proakis: Digital Communications. McGraw-Hill, 1983.

    Google Scholar 

  18. L.L. Scharf, H. Elliott: Aspects of Dynamic Programming in Signal and Image Processing. IEEE Trans, on Automatic Control, Vol. AC-26, Okt. 1981, S. 1018–1029.

    Article  Google Scholar 

  19. H. Tanaka, Y. Hirakawa, S. Kaneku: Recognition of Distorted Patterns Using the Viterbi Algorithm. IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol. PAMI-4, Jan. 1982, S. 18–25.

    Article  Google Scholar 

  20. D.J. Burr: Designing a Handwriting Reader, IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, Sept. 1983, S. 554–559.

    Article  Google Scholar 

  21. Burkhardt H., Schorb H.: Maximum-A-Posteriori Restoration of Images — An Application of the Viterbi Algorithm to Two-Dimensional Filtering. Proc. of the 6th Intern. Conf. on Pattern Recognition, München, Okt. 82, S. 98-101.

    Google Scholar 

  22. H. Schorb: Maximum-a-posteriori Restauration von Bildern mit endlichem Grauwertevorrat. Dissertation, Universität Karlsruhe, 1986.

    Google Scholar 

  23. B. Lamb: Untersuchung und Erprobung von Methoden der dynamischen Programmierung zur Konturfindung. Studienarbeit am Institut für Mess-und Regelungstechnik der Universität Karlsruhe, 1982.

    Google Scholar 

  24. H. Ney: Dynamic Programming as a Technique for Pattern Recognition. Proc. of the 6th Intern. Conf. on Pattern Recognition, München, Okt. 82, S. 1119-1125.

    Google Scholar 

  25. Burkhardt H., Barbosa L.C.: Contributions to the Application of the Viterbi-Algorithm. IBM Research Report, RJ 3377(40413) 1/22/82, San Jose, Ca. und IEEE Trans, on Information Theory, Vol. IT-31, Sept. 1985, S. 626–634.

    MathSciNet  Google Scholar 

  26. R.W. Gerchberg: Super-resolution through error energy reduction. Optica Acta, Vol. 21, 1974, S. 709–720.

    Article  Google Scholar 

  27. A. Papoulis: A New Algorithm in Spectral Analysis and Band-Limited Extrapolation. IEEE Trans, on Circuits and Systems, Vol. CAS-22, Sept. 1975, S. 735–742.

    Article  MathSciNet  Google Scholar 

  28. R.W. Schafer, R.M. Mersereau, M.A. Richards: Constrained Iterative Restoration Algorithms. Proc. of the IEEE, Vol. 69, April 1981, S. 432–450.

    Article  Google Scholar 

  29. D. Cahana, H. Stark: Bandlimited Image Extrapolation with Faster Convergence. Applied Optics, Vol. 20, Aug. 1981, S. 2780–2786.

    Article  Google Scholar 

  30. H. Stark, D. Cahana, H. Webb: Restoration of Arbitrary Finite-Energy Optical Objects from Limited Spatial and Spectral Information, Journ. Opt. Soc. Am., Vol. 71, Juni 1981, S. 635–642.

    Article  MathSciNet  Google Scholar 

  31. A. Levi, H. Stark: Image Restoration by the Method of Generalized Projections with Application to Restoration from Magnitude. Journ. Opt. Soc. Am. A, Vol. 1, Sept. 1984, S. 932–943.

    Article  MathSciNet  Google Scholar 

  32. D.C. Youla: Generalized Image Restoration by the Method of Alternating Orthogonal Projections. IEEE Trans, on Circuits and Systems, Vol. CAS-25, Sept. 1978, S. 694–702.

    Article  MathSciNet  Google Scholar 

  33. A.K. Katsaggelos, J. Biemond, R.M. Mersereau, R.W. Schafer: An Iterative Method for Restoring Noisy Blurred Images. Circuits, Systems, and Signal Processing, Vol. 3, 1984, S. 139–160.

    Article  MATH  Google Scholar 

  34. R.T. Chin, C.-L. Yeh, W.S. Olson: Restoration of Multichannel Microwave Radiometric Images. IEEE Trans, on Pattern Analysis and Machine Intelligence, Vol. PAMI-7, Juli 1985, S. 475–484.

    Article  Google Scholar 

  35. R. Prost, R. Goutte: Discrete Constrained Iterative Deconvolution Algorithms with Optimized Rate of Convergence. Signal Processing, 7(1984), S. 209–230.

    Article  MathSciNet  Google Scholar 

  36. L.R. Bahl, F. Jelinek, R.L. Mercer: A Maximum-Likelihood Approach to Continuous Speech Recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. PAMI-5, März 1983, S. 179–190.

    Article  Google Scholar 

  37. J.R. Fienup: Phase Retrieval Algorithms: A Comparison. Appl. Opt., Vol. 21, 1982, S. 2758-2769.

    Google Scholar 

  38. Müller X., Burkhardt: Two-Dimensional, Fast Translation Invariant Transforms with Improved Mapping Properties. Proc. of the 6th Intern. Conf. on Pattern Recognition, München, Okt. 82, S. 427-430.

    Google Scholar 

  39. Müller X.: Schnelle translationsinvariante Transformationen zur Bearbeitung digitaler Grauwertbilder. Dissertation, Universität Karlsruhe. Ersch. als Fortschrittbericht (Reihe 10, Nr. 17) der VDI-Zeitschriften, VDI-Verlag, Okt. 79.

    Google Scholar 

  40. Frydrychowicz S.: Anwendungen der Gruppentheorie auf Probleme der Mustererkennung. Dissertation, Universität Karlsruhe. Ersch. als Fortschrittbericht (Reihe 10, Nr. 42) der VDI-Zeitschriften, VDI-Verlag, Febr. 85.

    Google Scholar 

  41. Burkhardt H., Schorb H.: Sichtprüfung bei Digitalanzeigen. Tagungsband der VDI/VDE-GMR-Fachtagung “Automatisierte Meßsysteme”, Fellbach, Nov. 85, VDI-Bericht 566.

    Google Scholar 

  42. Wagh M.D., Kanetkar S.V.: A Class of Translation Invariant Transforms. IEEE Trans, on Acoustics, Speech, and Signal Processing, Vol. ASSP-25, Apr. 1977, S. 203–205.

    Article  Google Scholar 

  43. H.S. Stone: Parallel Processing with the Perfect Shuffle. IEEE Trans. Comp., Vol. C-20, Febr. 1971, S. 153–161.

    Article  Google Scholar 

  44. Beth T.: Verfahren der schnellen Fourier-Transformation. Teubner Verlag, 1984.

    Google Scholar 

  45. Beth T.: Finite Version of the Radon-Transform, Based on Finite Geometric Structures. Lect. Notes Med. Info., 8(1981), S. 7–12.

    MathSciNet  Google Scholar 

  46. N. Canterakis: Magnitude-Only Reconstruction of Two-Dimensional Sequences of Finite Regions of Support. IEEE Trans, on Acoustics, Speech, and Signal Processing, Vol. ASSP-31, Okt. 1983, S. 1256–1262.

    Article  Google Scholar 

  47. J.H. McClellan, CM. Rader: Number Theory in Digital Signal Processing. Prentice-Hall, 1979.

    Google Scholar 

  48. J.B. Martens: Convolution Algorithms, Based on the CRT (Chinese Remainder Theorem). Signal Processing 6(1984), S. 279–292.

    Article  MathSciNet  MATH  Google Scholar 

  49. Cooley W.T., Tukey J. W.: An Algorithm for Machine Computation of Complex Fourier Series. Mathematics of Computation 19(1965), S. 297–301.

    Article  MathSciNet  MATH  Google Scholar 

  50. N. Ahmed, K.R. Rao: Orthogonal Transforms for Digital Signal Processing. Springer Verlag, 1975.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Arbeitsbereich Technische Informatik I, Technische Universität Hamburg-Harburg, Postfach 901403, D-2100, Hamburg 90, Deutschland

    Hans Burkhardt

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  1. Hans Burkhardt
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Editors and Affiliations

  1. Fachbereich 14 Elektrotechnik, Universität-Gesamthochschule-Paderborn, Pohlweg 47–49, 4790, Paderborn, Deutschland

    Georg Hartmann

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© 1986 Springer-Verlag Berlin Heidelberg

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Burkhardt, H. (1986). Methoden der Digitalen Signalverarbeitung in der Bildverarbeitung und Mustererkennung. In: Hartmann, G. (eds) Mustererkennung 1986. Informatik-Fachberichte, vol 125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-71387-3_9

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  • DOI: https://doi.org/10.1007/978-3-642-71387-3_9

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  • Print ISBN: 978-3-540-16812-6

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