THRESHOLD DECOMPOSITION DRIVEN ADAPTIVE MORPHOLOGICAL FILTER FOR IMAGE SHARPENING

Tarek A. Mahmoud, Stephen Marshall

Abstract

A new method is proposed to sharpen digital images. This sharpening method is based on edge detection and a class of morphological filtering. Motivated by the success of threshold decomposition, gradient-based operators, such as Prewitt operators, are used to detect the locations of the edges. A morphological filter is used to sharpen these detected edges. Experimental results demonstrate that the performance of these detected edge deblurring filters is superior to that of the traditional sharpening filter family.

References

  1. Arce, G. R., 1998. A general weighted median filter structure admitting negative weights. IEEE Trans. Signal Processing 46 (12), 3195-3205.
  2. Blackledge, J., 1989. Quantitative Coherent Imaging, Academic Press. London.
  3. Fischer, M., Paredes, J. L., Arce, G. R., 2002. Weighted median image sharpeners for the world wide web. IEEE Trans. Image Processing 11 (7), 717-727.
  4. Fitch, J. P., Coyle, E. J., Gallagher, N. C., 1984. Median filtering by threshold decomposition. IEEE Trans. Acoustic, Speech and Signal Processing, 32 (6), 1183- 1188.
  5. Hardie, R. C., Boncelet, C. G., 1993. LUM filters: A class of rank-order-based filters for smoothing and sharpening. IEEE Trans. Signal Processing 41 (3), 1061-1076.
  6. Kramer, H. P., Bruckner, J. B., 1975. Iterations of a nonlinear transformation for enhancement of digital images. Pattern Recognition 7, 53-58.
  7. Lee, Y. H., Fam, A. T., 1987. An edge gradient enhancing adaptive order statistic filter. IEEE Trans. Acoustic, Speech, Signal Processing 35, 1061-1076.
  8. Maragos, P., 2005. Morphological filtering for image enhancement and feature detection, in: Bovik, A. C. (Eds.), The Image and Video Processing Handbook, Elsevier Academic Press. pp 135-156.
  9. Paredes, J. L., Arce, G. R., 1999. Stack filter, stack smoothers, and mirrored threshold decomposition. IEEE Trans. Signal Processing 47 (10), 2757-2767.
  10. Pitas, I., 1993. Digital Image Processing Algorithms, Prentice Hall.
  11. Pratt, W. K., 1978. Digital Image Processing, Wiley. New York.
  12. Prewitt, J. M., 1970. Object enhancement and extraction. Picture Processing and Psychopictorics, 75-149.
  13. Schavemaker, J. G., Reinders, M. J., Gerbrands, J. J., Backer, E., 2000. Image sharpening by morphological filtering. Pattern Recognition 33, 997-1012.
  14. Serra, J., 1982. Image Analysis and Mathematical Morphology, Academic Press. New York.
  15. Van den Boomgaard, R., Dorst, L., Makram-Ebeid, S., Schavemaker, J. G., 1996. Quadratic structuring functions in mathematical morphology. in: Maragos, P., Schafer, R. W., Butt, M. A. (Eds.), Mathematical Morphology and its Applications to Image and Signal Processing, Kluwer Academic Publishers. pp. 147- 154.
Download


Paper Citation


in Harvard Style

A. Mahmoud T. and Marshall S. (2007). THRESHOLD DECOMPOSITION DRIVEN ADAPTIVE MORPHOLOGICAL FILTER FOR IMAGE SHARPENING . In Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, ISBN 978-972-8865-73-3, pages 40-45. DOI: 10.5220/0002048400400045


in Bibtex Style

@conference{visapp07,
author={Tarek A. Mahmoud and Stephen Marshall},
title={THRESHOLD DECOMPOSITION DRIVEN ADAPTIVE MORPHOLOGICAL FILTER FOR IMAGE SHARPENING},
booktitle={Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,},
year={2007},
pages={40-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002048400400045},
isbn={978-972-8865-73-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP,
TI - THRESHOLD DECOMPOSITION DRIVEN ADAPTIVE MORPHOLOGICAL FILTER FOR IMAGE SHARPENING
SN - 978-972-8865-73-3
AU - A. Mahmoud T.
AU - Marshall S.
PY - 2007
SP - 40
EP - 45
DO - 10.5220/0002048400400045