IJMTES – IMAGE RETRIEVAL USING DIFFERENT TYPES OF INTERPOLATION TECHNIQUES

Journal Title : International Journal of Modern Trends in Engineering and Science

Paper Title : IMAGE RETRIEVAL USING DIFFERENT TYPES OF INTERPOLATION TECHNIQUES   

Author’s Name : Minakshi R Singh | Prof A S Bhideunnamed

Volume 04 Issue 02 2017

ISSN no:  2348-3121

Page no: 1-5

Abstract – Interpolation is the process of changing image from one resolution to another without losing the image quality. Enhancement of image, zooming, resizing any many more are very important function of image interpolation method in image processing. Here in this paper, different interpolation algorithms have been reviewed. We have implemented all reviewed interpolation algorithms on matlab with the image of different size and different resolution and done comparison of all on PSNR, MSE, MAXERR, L2RAT and Time.  This paper gives idea about different interpolation techniques like Nearest Neighbor, Bi-Linear, Bi-Cubic, and B-Spline to be used as per the requirement.

Keywords— Image, Interpolation, Enhancement, PSNR, MSE, Time

Reference

  1. S. H. Mahajan and V. K. Harpale, “Adaptive and Non-adaptive Image Interpolation Techniques,” 2015 International Conference on Computing Communication Control and Automation, Pune, 2015, pp. 772-775.
  2. O. Rukundo and B. T. Maharaj, “Optimization of image interpolation based on nearest neighbour algorithm,” 2014 International Conference on Computer Vision Theory and Applications (VISAPP), Lisbon, Portugal, 2014, pp. 641-647.
  3. Zhou Dengwen and Shen Xiaoliu, “An Effective Color Image Interpolation Algorithm”, IEEE 4th International Congress on Image and Signal Processing, pp 984-988, 2011.
  4. Ramesh Kumar lama, Moo-Rak Choi, Jong-Woo Kim, Jae-Young Pyun, and Goo-Rak kwon, “Color Image Interpolation for High Resolution Display Based on Adaptive Directional Lifting based Wavelet Transform”, IEEE International Conference on Consumer Electronics (ICCE), pp 219-221, 2014.
  5. Sasikala S. and Sudhakar Putheti, “Interpolation of CFA Color Images with Hybrid Image Denoising”, Sixth International Conference on Computational Intelligence and Communication Networks, pp 193-197, 2014.
  6. Lei Zhang and Xiaolin Wu, “An edge-guided image interpolation algorithm via directional filtering and data fusion,” in IEEE Transactions on Image Processing, vol. 15, no. 8, pp. 2226-2238, Aug. 2006.
  7. Chen, Mei-Juan, Chin-Hui Huang, and Wen-Li Lee. “A fast edge-oriented algorithm for image interpolation.” Image and Vision Computing 23.9 (2005): pp 791-798.
  8. R. Lukac, K. Martin, and K.N. Plataniotis, “Digital Camera Zooming Based on Unified CFA Image Processing Steps”, IEEE Transactions on Consumer Electronics, Vol. 50, No. 1, pp-15-24, 2004.
  9. Hongjian Shi and R. Ward, “Canny edge based image expansion,” 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353), 2002, pp. I-785-I-788 vol.1.
  10. G.J. Grevera and J.K. Udupa, “Shape-Based Interpolation of Multidimensional Grey-Level Images”, IEEE Transactions on Medical Imaging, vol. 15,pp. 881-892,December, 1996.
  11. D. Zhou and Shen Xiaoliu, “An effective color image interpolation algorithm,” 2011 4th International Congress on Image and Signal Processing, Shanghai, 2011, pp. 984-988.
  12. C. M. Zwart and D. H. Frakes, “Soft adaptive gradient angle interpolation of grayscale images,” 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, 2012, pp. 845-848.
  13. M. Hajizadeh, M. S. Helfroush and A. Tashk, “Improvement of image zooming using least directional differences based on linear and cubic interpolation,” 2009 2nd International Conference on Computer, Control and Communication, Karachi, 2009, pp. 1-6.
  14. Min Sheng, Benyue Su, Wanbao Hu and Gongqin Zhu, “A class of image interpolation method based on quasi Hermite interpolation spline,” 2008 International Conference on Audio, Language and Image Processing, Shanghai, 2008, pp. 520-524.
  15. Zhenhua Mai, Jeny Rajan, Marleen Verhoye and Jan Sijbers, “Robust edge-directed interpolation of magnetic resonance images,” 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), Shanghai, 2011, pp. 472-476.
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