Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Wavelet domain image resolution enhancement

Wavelet domain image resolution enhancement

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:
 
 
 
 
 
IEE Proceedings - Vision, Image and Signal Processing — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A wavelet-domain image resolution enhancement algorithm which is based on the estimation of detail wavelet coefficients at high resolution scales is proposed. The method exploits wavelet coefficient correlation in a local neighbourhood sense and employs linear least-squares regression to estimate the unknown detail coefficients. Results show that the proposed method is considerably superior to conventional image interpolation techniques, both in objective and subjective terms, while it also compares favourably with competing methods operating in the wavelet domain.

References

    1. 1)
      • Kinebuchi, K., Muresan, D.D., Parks, T.W.: `Image interpolation using wavelet-based hidden Markov trees', Proc. ICASSP01, May 2001, 3, p. 7–11.
    2. 2)
      • C. Ford , D.M. Etter . Wavelet basis reconstruction of nonuniformly sampled data. IEEE Trans. Circuits Syst. , 8 , 1165 - 1168
    3. 3)
    4. 4)
    5. 5)
      • Chang, S.G., Cvetkovic, Z., Vetterli, M.: `Resolution enhancement of images using wavelet transform extrema extrapolation', Proc. ICASSP95, May 1995, 4, p. 2379–2382.
    6. 6)
      • Nguyen, N.: `Numerical techniques for image superresolution', 2000, PhD, Stanford University.
    7. 7)
      • A. Said , W.A. Pearlman . A new fast and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. Circuits Syst. , 243 - 250
    8. 8)
      • W.K. Carey , D.B. Chuang , S.S. Hemami . Regularity-preserving image interpolation. IEEE Trans. Image Process. , 9 , 1295 - 1297
    9. 9)
      • Zhao, S., Han, H., Peng, S.: `Wavelet domain HMT-based image superresolution', Proc. ICIP03, Sept. 2003, 2, p. 933–936.
    10. 10)
      • Mitevski, S., Bogdanov, M.: `Application of multiresolutional basis fitting reconstruction in image magnifying', Proc. 9th Telecommunications Forum TELFOR 2001, Nov. 2001, p. 565–568.
    11. 11)
      • Nguyen, N., Milanfar, P.: `An efficient wavelet-based algorithm for image superresolution', Proc. ICIP00, Sept. 2000, 2, p. 351–354.
http://iet.metastore.ingenta.com/content/journals/10.1049/ip-vis_20045056
Loading

Related content

content/journals/10.1049/ip-vis_20045056
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address