CFP last date
20 June 2024
Reseach Article

Pixel Dependent Automatic Parameter Selection for Image Denoising with Bilateral Filter

by C. Shyam Anand, J. S. Sahambi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 45 - Number 10
Year of Publication: 2012
Authors: C. Shyam Anand, J. S. Sahambi
10.5120/6820-9180

C. Shyam Anand, J. S. Sahambi . Pixel Dependent Automatic Parameter Selection for Image Denoising with Bilateral Filter. International Journal of Computer Applications. 45, 10 ( May 2012), 41-46. DOI=10.5120/6820-9180

@article{ 10.5120/6820-9180,
author = { C. Shyam Anand, J. S. Sahambi },
title = { Pixel Dependent Automatic Parameter Selection for Image Denoising with Bilateral Filter },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 45 },
number = { 10 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 41-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume45/number10/6820-9180/ },
doi = { 10.5120/6820-9180 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:37:19.296297+05:30
%A C. Shyam Anand
%A J. S. Sahambi
%T Pixel Dependent Automatic Parameter Selection for Image Denoising with Bilateral Filter
%J International Journal of Computer Applications
%@ 0975-8887
%V 45
%N 10
%P 41-46
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image denoising using bilateral filter is controlled by the width of its smoothing functions namely the domain and the range components. The choice of the width of range function is image dependent and requires several experiments. This paper presents an automatic method based on power-law scaling of the inverse of local statistics for pixel wise estimation of range parameter. This leads to an adaptive range function that is narrow along the edges and wide for smooth regions. The experimental results validate the performance of the proposed method of parameter selection in denoising images corrupted by additive white Gaussian noise.

References
  1. M. Elad, "On the Origin of the Bilateral Filter and Ways to Improve it," IEEE Transaction on Image Processing, vol. 11, no. 10, pp. 1141–1151, October 2002.
  2. C. Tomasi and R. Manduchi, "Bilateral Filtering for Gray and Color Images," in Proc. 6th Int. Conf. Computer Vision, 1998, pp. 839–846.
  3. S. Paris, P. Kornprobst, J. Tumblin, and F. Durand, Bilateral Filtering: Theory and Applications, Foundations and Trends in Computer Graphics and Vision. Now publishers Inc. , 2008, vol. 4, no. 1.
  4. D. Barash, "A Fundamental Relationship between Bilateral Filtering, Adaptive Smoothing, and the Nonlinear Diffusion Equation," IEEE Transaction on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 844–847, June 2002.
  5. J. -W. Han, J. -H. Kim, S. -H. Cheon, and J. -O. Kim, "A Novel Image Interpolation Method Using the Bilateral Filter," IEEE Transactions on Consumer Electronics, vol. 56, no. 1, pp. 175–181, Feb. 2010.
  6. L. Qiegen, L. Jianhua, and Z. Yuemin, "Adaptive Image Decomposition by Improved Bilateral Filter," International Journal of Computer Applications, vol. 23, pp. 16–22, 2011.
  7. C. Liu, W. T. Freeman, R. Szeliski, and S. B. Kang, "Noise Estimation from a Single Image," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 901–908, 2006.
  8. M. Zhang and B. K. Gunturk, "Multiresolution Bilateral Filtering for Image Denoising," IEEE Transactions on Image Processing, vol. 17, no. 12, pp. 2324–2333, Dec. 2008.
  9. A. Wong, "Adaptive bilateral filtering of image signals using local phase characteristics," Signal Processing, vol. 88, no. 6, pp. 1615–1619, June 2008.
  10. B. Zhang and J. P. Allebach, "Adaptive Bilateral Filter for Sharpness Enhancement and Noise Removal," IEEE Transactions on Image Processing, vol. 17, no. 5, pp. 664–678, May 2008.
  11. A. Gabiger-Rose, M. Kube, P. Schmitt, R. Weigel, and R. Rose, "Image denoising using bilateral filter with noise-adaptive parameter tuning," in IECON 2011. IEEE Industrial Electronics Society, Nov. 2011, pp. 4515–4520.
  12. J. Lee, "Refined Filtering of Image Noise using Local Statistics," Computer Graphics and Image Processing, vol. 15, pp. 380–389, 1981.
  13. J. -S. Lee, "Digital Image Enhancement and Noise Filtering by use of Local Statistics," IEEE Transactions on Pattern Analysis and Machine Intelligence. , vol. 2, no. 2, pp. 165–168, March 1980.
  14. R. C. Gonzalez, Digital Image Processing, 2nd ed. Pearson Education, 2004.
  15. P. C. Hansen, J. G. Nagy, and D. P. O'Leary, Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3). SIAM, 2006.
  16. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, "Image quality assessment: From error visibility to structural similarity," IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, April 2004
Index Terms

Computer Science
Information Sciences

Keywords

Automatic Parameter Selection Bilateral Filter Denoising Local Statistics Pixel Adaptive