http://iet.metastore.ingenta.com
1887

Morphological operators

Morphological operators

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The author and colleagues have already proved that mediated morphological filters (MEDMFs) remove speckle, Gaussian or salt&pepper noise better than classical morphological filters (MFs) and linear methods. They have also demonstrated the dominance of MEDMFs in a multiple noisy environment compared with MFs and linear filters. Here, they describe novel new research that has led to new morphological operators being successfully devised, the performance of which is better than MEDMFs for both single and multiple denoising. The new operators employ a special combination of weighted median filters and MFs.

References

    1. 1)
      • F. Gerritsen , L.G. Aardema . Design and use of DIP-1: a last flexible and dynamically microprogrammable image processor. Pattern Recognit. , 319 - 330
    2. 2)
      • J.C. Klein , L. Cahn , C. Ray , G.H. Urban . The texture analyser. J. Microsc. , 349 - 356
    3. 3)
      • M. Duff , M. Duff . (1979) Parallel processors for digital image processing, Advances in digital image processing.
    4. 4)
      • M.H. Sedaaghi . ECG wave detection using morphological filters. Appl. Signal Process. , 182 - 194
    5. 5)
      • P. Maragos , R.W. Schafer . Morphological filters – Pt I: Their set-theoretic analysis and relations to linear shift-invariant filters. IEEE Trans. Acoust. Speech Signal Process. , 8 , 1153 - 1169
    6. 6)
      • J. Serra . (1992) Image analysis and mathematical morphology.
    7. 7)
      • Heijmans, H.J.A.M.: `Morphological filters', Proc. of Summer School on Morphological Image and Signal Processing, 1995, Zakopane, Poland.
    8. 8)
      • Sedaaghi, M.H., Dai, R., Khosravi, M.: `Mediated morphological filters', Proc. of 2001 Int. Conf. on Image Processing, October 2001, Thessaloniki, Greece, IEEE Signal Processing Society, III, p. 692–695.
    9. 9)
      • S.K. Mitra , G.L. Sicuranza . (2001) Nonlinear image processing.
    10. 10)
      • R.M. Haralick , S.R. Sternberg , X. Zhuang . Imageanalysis using mathematical morphology. IEEE Trans. Pattern Anal.Mach. Intell. , 4 , 532 - 550
    11. 11)
      • P. Maragos . A representation theory for morphological image and signal processing. IEEE Trans. Pattern Anal. Mach. Intell. , 6 , 586 - 599
    12. 12)
      • M.H. Sedaaghi , Q.H. Wu . Weighted morphological filter. Electron. Lett. , 16 , 1566 - 1567
http://iet.metastore.ingenta.com/content/journals/10.1049/el_20020943
Loading

Related content

content/journals/10.1049/el_20020943
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address