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Reseach Article

Combined Method of Two Stage LPG-PCA Denoising with Impact on Preprocessing Step for Noisy Images

by Jansirani S, Karthikeyan S, Kiruba Priyadharsihni V
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 83 - Number 11
Year of Publication: 2013
Authors: Jansirani S, Karthikeyan S, Kiruba Priyadharsihni V
10.5120/14496-2881

Jansirani S, Karthikeyan S, Kiruba Priyadharsihni V . Combined Method of Two Stage LPG-PCA Denoising with Impact on Preprocessing Step for Noisy Images. International Journal of Computer Applications. 83, 11 ( December 2013), 36-41. DOI=10.5120/14496-2881

@article{ 10.5120/14496-2881,
author = { Jansirani S, Karthikeyan S, Kiruba Priyadharsihni V },
title = { Combined Method of Two Stage LPG-PCA Denoising with Impact on Preprocessing Step for Noisy Images },
journal = { International Journal of Computer Applications },
issue_date = { December 2013 },
volume = { 83 },
number = { 11 },
month = { December },
year = { 2013 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume83/number11/14496-2881/ },
doi = { 10.5120/14496-2881 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:59:08.223187+05:30
%A Jansirani S
%A Karthikeyan S
%A Kiruba Priyadharsihni V
%T Combined Method of Two Stage LPG-PCA Denoising with Impact on Preprocessing Step for Noisy Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 83
%N 11
%P 36-41
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image denoising plays a vital role in many image processing application to reduce the noise level without affecting the original image features. In this paper a powerful image denoising algorithm LPG-PGA with preprocessing step like Diffusion is introduced to improve the quality of the image. Per-processing step like diffusion is a necessary one in-case of noise is an important consideration, where the diffusion filter has strong smoothing characteristics [4-5]. PCA is statistical techniques which can be used to reduce the dataset from higher dimension to lower dimension without huge loss of image features [1]. The proposed system performance is evaluated by using various types of objective metrics like PSNR, SSIM, MSE, LMSE and NAE. The result shows that the proposed method has good promising performance compare to existing method.

References
  1. Lei Zhang, Weisheng Dong, David Zhang, and Guangming Shi, "Two-stage image denoising by principal component analysis with local pixel grouping", Elsevier, Pattern Recognition 43 (2010), 1531–1549.
  2. K. John Peter, Dr K. Senthamarai Kannan, Dr S. Arumugan, and G. Nagarajan, "Two-stage image denoising by Principal Component Analysis with Self Similarity pixel Strategy", International Journal of Computer Science and Network Security, VOL. 11 No. 5, May 2011.
  3. Sabita Pal, Rina Mahakud, and Madhusmita Sahoo, "PCA based Image Denoising using LPG", IJCA Special Issue on "2nd National Conference- Computing, Communication and Sensor Network", 2011.
  4. Ahmed Badawi, J. Michael Johnson, and Mohamed Mahfouz Scatterer Density in Edge and Coherence Enhancing Nonlinear Anisotropic Diffusion for Medical Ultrasound Speckle Reduction, International Journal of Biological and Life Sciences, 2007.
  5. Joachim Weickert, Anisotropic Diffusion in Image Processing, Department of Computer Science University of Copenhagen Copenhagen, Denmark.
  6. Erkut Erdem, Linear Diffusion, Hacettepe University, February 24th, 2012.
  7. Aditya Goyal, Akhilesh Bijalwan, Mr. Kuntal Chowdhury, A Comprehensive Review of Image Smoothing Techniques, International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, Issue 4, June 2012.
  8. Haixia Wang, Qian Kemao, Wenjing Gao, Feng Lin, Hock Soon Seah, " Partial Differential Equation Based Coherence Enhancing Denoising for Fringe Patterns", International Conference on Experimental Mechanics 2008, Vol. 7375, 2008.
  9. Weickert J. , "Coherence-Enhancing Diffusion Filtering", International Journal of Computer Vision", vol. 31, issue 2-3, pp. 111 - 127 (1999).
  10. Weickert J. , V. Hlavac and R. Sara, Eds, "Multiscale Texture Enhancement", Computer analysis of images and patterns, Lecture Notes in Comp. Science, 970, Springer, Berlin, pp. 230-236(1995).
  11. Asha Ashok, Dhivya S, Jansirani S, K. P. Soman, Combined Method of Level set with impact on Pre-processing for binarization of document images in Tamil Script, IJCA Journal, Volume 48, 2012.
  12. L. Zhang, B. Paul, X. Wu, Hybrid inter- and intra-wavelet scale image restoration, Pattern Recognition 36 (8) (2003) 1737–1746.
  13. D. Barash, A fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation, IEEE Transaction on Pattern Analysis and Machine Intelligence, 24 (6) (2002) 844–847.
  14. D. D. Muresan, T. W. Parks, Adaptive principal components and image denoising, in: Proceedings of the 2003 International Conference on Image Processing, 14–17 September, vol. 1, 2003, pp. I101–I104.
  15. Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE Transaction on Image Processing 13 (4) (2004).
Index Terms

Computer Science
Information Sciences

Keywords

LPG-PCA denoising Edge enhancing diffusion.