Skip to main content
Springer Nature Link
Log in

Hybrid-Thresholding based Image Super-Resolution Technique by the use of Triplet Half-Band Wavelets

  • Original Contribution
  • Published:
Journal of The Institution of Engineers (India): Series B Aims and scope Submit manuscript

Abstract

This paper presents a modified image super-resolution scheme based on the wavelet coefficients hybrid-thresholding by the use of triplet half-band wavelets (THW) derived from the generalized half-band polynomial. At first, discrete wavelet transform (DWT) is obtained from triplet half-band kernels and it applied on the low-resolution image to obtain the high frequency sub-bands. These high frequency sub-bands and the original low-resolution image are interpolated to enhance the resolution. Second, stationary wavelet transform is obtained by using THW, which is employed to minimize the loss due to the use of DWT. In addition, hybrid thresholding scheme on wavelet coefficients scheme is proposed on these estimated high-frequency sub-bands in order to reduce the spatial domain noise. These sub-bands are combined together by inverse discrete wavelet transform obtained from THW to generate a high-resolution image. The proposed approach is validated by comparing the quality metrics with existing filter banks and well-known super-resolution scheme.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
€32.70 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (France)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. P.P. Gajjar, M.V. Joshi, New-learning bases super-resolution: use of DWT and IGMRF prior. IEEE Trans. Image Process. 15(5), 1201–1213 (2010)

    Article  MathSciNet  Google Scholar 

  2. C.V. Jiji, M.V. Joshi, S. Chaudhari, Single-frame image super-resolution using learned wavelet coefficients. Int. J. Imaging Syst. Technol. 14(3), 105–112 (2004)

    Article  Google Scholar 

  3. R.Y. Tsai, T.S. Huang, Multiple Frame Image Restoration and Registration, Advances in Computer Vision and Image Processing (JAI Press, Greenwich, 1984), pp. 317–339

    Google Scholar 

  4. M. Irani, S. Peleg, Motion analysis for image enhancement resolution, occlusion, and transparency. J. Vis. Commun. Image Represent. 4, 324–335 (1993)

    Article  Google Scholar 

  5. H. Ji, C. Fermullar, Robust wavelet-based super-resolution reconstruction. IEEE Trans. Pattern Anal. Mach. Intell. 34(4), 649–660 (2009)

    Article  Google Scholar 

  6. N. Nguyen, N.P. Milanfar, A wavelet-based interpolation–restoration method for super-resolution. Circuits Syst. Signal Process. 19, 321–338 (2000)

    Article  MATH  Google Scholar 

  7. G. Anbarjafari, H. Demirel, Image Super resolution based on interpolation of wavelet domain high frequency sub-bands and the spatial domain input image. Electron. Telecommun. Res. Inst. J. 32(3), 390–394 (2010)

    Google Scholar 

  8. H. Demirel, G. Anbarjafari, Image resolution enhancement by using discrete and stationary wavelet decomposition. IEEE Trans. Image Process. 20(5), 1458–1460 (2011)

    Article  MathSciNet  Google Scholar 

  9. M.B. Chappalli, N.K. Bose, Simultaneous noise filtering and super-resolution with second-generation wavelets. IEEE Signal Process. Lett. 2(1), 772–775 (2005)

    Article  Google Scholar 

  10. N.K. Bose, M.B. Chappalli, Super-resolution with second generation wavelets. Sig. Process. Image Commun. 19(5), 387–391 (2004)

    Article  Google Scholar 

  11. S. Zhao, H. Han, S. Peng, Wavelet domain HMT-based image super resolution. Proc. IEEE Int. Conf. Image Process. 2, 933–936 (2003)

    Google Scholar 

  12. B.D. Patil, P.G. Patwardhan, V.M. Gadre, On the design of FIR wavelet filter banks using factorization of a half-band polynomial. IEEE Signal Process. Lett. 15, 485–488 (2008)

    Article  Google Scholar 

  13. S.M. Phoong, C.W. Kim, P.P. Vaidyanathan, R. Ansari, A new class of two-channel biorthogonal filter banks and wavelet bases. IEEE Trans. Signal Process. 43(3), 649–665 (1995)

    Article  Google Scholar 

  14. R. Ansari, C.W. Kim, M. Dedovic, Strcture and design of two-channel filter banks derived from a triplet of halfband filtres. IEEE Trans. Cirucuits Syst. II Analog Digit. Signal Process. 46(12), 1487–1496 (1999)

    Article  Google Scholar 

  15. D.B.H. Tay, M. Palaniswami, A novel approach to the design of the class of triplet halfband filterbanks. IEEE Trans. Circuits Syst. II Express Briefs 51(7), 378–383 (2004)

    Article  Google Scholar 

  16. S.C. Chan, K.S. Yeung, On the design and multiplierless realization of perfect reconstruction triplet-based FIR filter banks and wavelet bases. IEEE Trans. Circuits Syst. I 51(8), 1476–1491 (2004)

    Article  MathSciNet  Google Scholar 

  17. H.H. Kha, H.D. Tuan, T.Q. Nguyen, Optimal design of FIR triplet halfband filter bank and application in image coding. IEEE Trans. Image Process. 22(2), 586–591 (2011)

    Article  MathSciNet  Google Scholar 

  18. A.D. Rahulkar, R.S. Holambe, Half-Iris feature extraction and recognition using a new class of biorthogonal triplet half-band filter bank and flexible k-out-of-n: a post-classifier. IEEE Trans. Inf. Forensic Secur. 7(1), 230–241 (2012)

    Article  Google Scholar 

  19. P.P. Vaidyanathan, Multirate Systems and Filter Banks (Prentice-Hall, Englewood Cliffs, 1993)

    MATH  Google Scholar 

  20. M. Vetterli, J. Kovacevic, Wavelets and Sub-band Coding (Prentice-Hall, EnglewoodClifs, 1995)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Modern Education Society’s College of Engineering, Pune, Maharastra, India

    Pravin B. Chopade

  2. National Institute of Technology Goa, Ponda, Goa, India

    Amol D. Rahulkar

  3. Kalyan Jadhav’s Educational Institutes, Pune, Maharastra, India

    Pradeep M. Patil

Authors
  1. Pravin B. Chopade
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Amol D. Rahulkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pradeep M. Patil
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pravin B. Chopade.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chopade, P.B., Rahulkar, A.D. & Patil, P.M. Hybrid-Thresholding based Image Super-Resolution Technique by the use of Triplet Half-Band Wavelets. J. Inst. Eng. India Ser. B 97, 517–523 (2016). https://doi.org/10.1007/s40031-016-0244-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40031-016-0244-6

Keywords

Search

Navigation