International Journal of Information Technology and Computer Science (IJITCS)
IJITCS Vol. 4, No. 9, 8 Aug. 2012
Cover page and Table of Contents: PDF (size: 767KB)
Image Denoising Using Tri Nonlinear and Nearest Neighbor Interpolation with Wavelet Transform
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Author(s)
Index Terms
Noise, Tri non linear Interpolation, Nearest Neighbor interpolation, Wavelet
Abstract
In this paper new methods Tri Non Linear Interpolation and nearest neighbor interpolation for image denoising in wavelet domain are proposed. Tri non linear interpolation methods better de-noising method which preserves the image feature like edges and background. Interpolation is way through which images are enlarged. The nearest neighbor interpolation used forward wavelet and enlarges the size of image which retains the image parameter. The nearest neighbor interpolation technique is fruit full for variety of noisy images. PSNR is key parameter for measurement of image quality throughout this text. The existing methods used the threshold technique for noise removal but our methods image quality is better as compared to the existing threshold technique.
Cite This Paper
Sachin D Ruikar, Dharmpal D Doye, "Image Denoising using Tri Nonlinear and Nearest Neighbor Interpolation with Wavelet Transform", International Journal of Information Technology and Computer Science(IJITCS), vol.4, no.9, pp.36-44, 2012. DOI:10.5815/ijitcs.2012.09.05
Reference
[1]Dan Su, Philip Willis, “Image Interpolation by Pixel Level Data-Dependent Triangulation”, Computer Graphics.
[2]Yohei Katsuyama and Kaoru Arakawa, “Color Image Interpolation for Impulsive Noise Removal Using Interactive Evolutionary Computing”, IEEE 2010, ISCIT 2010, pp-877-893.
[3]E. Maeland, “On the comparison of interpolation methods,” IEEE Trans. Med. Image., vol. MI-7, pp. 213–217, 1988.
[4]J. A. Parker, R. V. Kenyon, and D. E. Troxel, “Comparison of interpolating methods for image resampling,” IEEE Trans. Med. Image., vol. MI-2, pp. 31–39, 1983
[5]Thomas M. Lehmann,* Member, IEEE, Claudia Gonner, and Klaus Spitzer, “Survey: Interpolation Methods in Medical Image Processing”, IEEE Transactions on Medical Imaging, Vol. 18, No. 11, November 1999, Pp-1049-1075.
[6]http://idlastro.gsfc.nasa.gov/idl_html_help/Interpolation_Methods.html
[7]Yasuhide Wakabayashi and Akira Taguchi,” Impulsive Noise Removal Using Interpolation Technique in Color Images”, IEEE 2005, Proceedings of 2005 International Symposium on Intelligent Signal Processing and Communication Systems.
[8]Neil Toronto, Dan Ventura and Bryan S Morse, “Edge Inference for Image Interpolation”, IEEE2005, Proceedings of International Joint Conference on Neural Networks, Montreal, Canada, July 31 - August 4, 2005, pp-1782-1787.
[9]H Quang Luong, Alessandro Ledda and Wilfried Philips, “Non-Local Image Interpolation”, IEEE, ICIP 2006, pp693-696.
[10]ROBERT G. KEYS, “Cubic Convolution Interpolation for Digital Image Processing”, IEEE Transactions On Acoustics, Speech, And Signal Processing, Vol. Assp-29, No. 6, December 1981 pp 1153-1160.
[11]Shinfeng D. Lin, Nicholas H. Younan, Claybome D. Taylor, “Interpolation Techniques for Noisy Spectral Data” IEEE1991.
[12]Einar Maeland, “On the Comparison of Interpolation Methods”, IEEE Transactions on Medical Imaging, Vol. I, No 3, September 1988 Pp 213-217.
[13]Hyeokho Choi and Richard Baraniuk, “Interpolation and De-noising of No uniformly Sampled Data Using Wavelet-Domain Processing”, 1999 IEEE pp1645-1648.
[14]Jenghwa Chang, Harry L. Graber, and Randall L. Barbour, “Dependence of Image Quality on Image Operator and Noise for Optical Diffusion Tomography”, Journal of Biomedical Optics 3(2), 137–144 (April 1998).
[15]Jong-Woo Han, Jun-Hyung Kim, Sung-Hyun Cheon, Jong-Ok Kim, and Sung-Jea Ko, “A Novel Image Interpolation Method Using the Bilateral Filter”, IEEE2010.
[16]GUO Chao-feng, LI Meilian, “An Improved Image De-noising Algorithm Based on Wavelet Transform Modulus Maximum”, IEEE 2010, International Conference on Computer Application and System Modeling (ICCASM 2010)
[17]Bernd Jähne, “Digital Image Processing”, Springer-Verlag Berlin Heidelberg 2002 Printed in Germany.
[18]C Sidney Burrus, Ramesh A Gopinath, and Haitao Guo, “Introduction to wavelet and wavelet transforms”, Prentice Hall1997.
[19]S. Mallat, "A Wavelet Tour of Signal Processing", Academic, New York, second edition, 1999.
[20]R. C. Gonzalez and R. Elwood's, Digital Image Processing. Reading, MA: Addison-Wesley, 1993.
[21]M. Sonka, V. Hlavac, R. Boyle "Image Processing, Analysis, And Machine Vision". Pp10-210.
[22]Raghuveer M. Rao, A.S. Bopardikar, “Wavelet Transforms: Introduction to Theory and Application" Published by Addison-Wesley 2001 pp1-126.
[23]Arthur Jr Weeks, "Fundamental of Electronic Image Processing" PHI 2005.