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Efficient Lifting Scheme Based Super Resolution Image Reconstruction Using Low Resolution Images

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Advanced Computing, Networking and Informatics- Volume 1

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 27))

Abstract

Super resolution (SR) images can improve the quality of the multiple lower resolution images. it is constructed using raw images like noisy, blurred and rotated. In this paper, Super Resolution Image Reconstruction (SRIR) method is proposed for improving the resolution of lower resolution (LR) images. Proposed method is based on wavelet lifting scheme with Daubechies4 coefficients. Experimental results prove the effectiveness of the proposed approach. It is observed from the experiments that the resultant reconstructed image has better resolution factor, MSE and PSNR values.

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References

  1. Gonzalez, R.C., Woods, R.C.: Digital Image Processing. Prentice Hall (2002)

    Google Scholar 

  2. Jayaraman, S., Esakkirajan, S., Veerakumar, T.: Digital Image Processing.Tata McGraw Hill Education Pvt. Ltd. (2009)

    Google Scholar 

  3. Morales, A., Agili, S.: Implementing the SPIHT Algorithm in MATLAB. In: Proceedings of ASEE/WFEO International Colloquium (2003)

    Google Scholar 

  4. Hu, Y., et al.: Low quality fingerprint image enhancement based on Gabor filter. In: 2nd International Conference on Advanced Computer Control (2010)

    Google Scholar 

  5. Chaudhuri, S.: Super-resolution imaging. The Springer International Series in Engineering and Computer Science, vol. 632 (2001)

    Google Scholar 

  6. Kumar, C.N.R., Ananthashayana, V.K.: Super resolution reconstruction of compressed low resolution images using wavelet lifting schemes. In: Second International Conference on Computer and Electrical Engineering, pp. 629–633 (2009)

    Google Scholar 

  7. Castro, E.D., Morandi, C.: Registration of translated and rotated images using finite Fourier transform. IEEE Transactions on Pattern Analysis and Machine Intelligenc 9(5), 700–703 (1987)

    Article  Google Scholar 

  8. Malỳ, J., Rajmic, P.: DWT-SPIHT Image Codec Implementation.Department of telecommunications, Brno University of Technology, Brno, CzechRepublic

    Google Scholar 

  9. Solomon, C., Breckon, T.: Fundamentals of Digital Image Processing: A practical approach with examples in Matlab. Wiley (2011)

    Google Scholar 

  10. Jiji, C.V., Joshi, M.V., Chaudhuri, S.: Single-frame image super-resolutionusing learned wavelet coefficients. International Journal of Imaging Systems andTechnology 14(3), 105–112 (2004)

    Article  Google Scholar 

  11. Jensen, A., la Cour-Harbo, A.: Ripples in mathematics: The discrete wavelets transform. Springer (2001)

    Google Scholar 

  12. Ananth, A.G.: Comparison of SPIHT and Lifting Scheme Image CompressionTechniques for Satellite Imageries. International Journal of Computer Applications 25(3), 7–12 (2011)

    Article  Google Scholar 

  13. Wang, K., Chen, B., Wu, G.: Edge detection from high-resolution remotely sensed imagery based on Gabor filter in frequency domain. In: 18th International Conference on Geoinformatics (2010)

    Google Scholar 

  14. Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation,rotation, and scaleinvariant image registration. IEEE Transactionson Image Processing 5(8), 1266–1271 (1996)

    Article  Google Scholar 

  15. Zhu, Z., Lu, H., Zhao, Y.: Multi-scale analysis of odd Gabor transform for edge detection. In: First International Conference on Innovative Computing, Information and Control (2006)

    Google Scholar 

  16. Zhang, D., Jiazhonghe: Face super-resolution reconstruction and recognition from low –resolution image sequences. In: 2nd International Conference on Computer Engineering and Technology, pp. 620–624 (2010)

    Google Scholar 

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Correspondence to Sanwta Ram Dogiwal .

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Dogiwal, S.R., Shishodia, Y.S., Upadhyaya, A. (2014). Efficient Lifting Scheme Based Super Resolution Image Reconstruction Using Low Resolution Images. In: Kumar Kundu, M., Mohapatra, D., Konar, A., Chakraborty, A. (eds) Advanced Computing, Networking and Informatics- Volume 1. Smart Innovation, Systems and Technologies, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-07353-8_31

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  • DOI: https://doi.org/10.1007/978-3-319-07353-8_31

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07352-1

  • Online ISBN: 978-3-319-07353-8

  • eBook Packages: EngineeringEngineering (R0)

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