An ANN Based Two Pass-Two Phase Adaptive Filtering of a Digital Image Corrupted by SPN
|
10.5120/5009-7328 |
Prakash Ch. Dash, Nachiketa Tarasia, Manoj Kumar Mishra, Sarita Das and G B Mund. Article: An ANN Based Two Pass-Two Phase Adaptive Filtering of a Digital Image Corrupted by SPN. International Journal of Computer Applications 40(11):20-27, December 2012. Full text available. BibTeX
@article{key:article,
author = {Prakash Ch. Dash and Nachiketa Tarasia and Manoj Kumar Mishra and Sarita Das and G. B. Mund},
title = {Article: An ANN Based Two Pass-Two Phase Adaptive Filtering of a Digital Image Corrupted by SPN},
journal = {International Journal of Computer Applications},
year = {2012},
volume = {40},
number = {11},
pages = {20-27},
month = {December},
note = {Full text available}
}
Abstract
Images get contaminated due to different noises at various stages of processing and Salt and Pepper is one such noise. The noise removal approach used for filtering mainly differs in their basic methodologies, but the purpose is to suppress different types and percentage of noise. Some of the filtering schemes replace those corrupted pixels by indentifying the positions of the corrupted pixels in the observed noisy image, with the help of a noise detector, whereas others remove all the pixels irrespective of corruption. This paper investigates the former method in denoising a digital image through incorporation of an adaptive threshold into the noise detection process. The adaptive threshold value thus obtained is based on the noisy image characteristics and their statistics using LeNN (Legendre Neural Network) and the patterns of input image are taken to train FLANN (Functional Link Artificial Neural Network) corrupted by SPN(Salt & Pepper noise). Comparative analysis on standard images at different noise percentage shows that the proposed scheme outperforms the existing schemes in terms of PSNR (peak signal to noise ratio). Thus, the proposed method named as “Two pass- Two phase adaptive filtering mechanism” is feasible and also makes it an efficient filter to restore the gray image fairly well preserving the quality of the filtered image, and also provides a better visual perception.
References
- . R. C. Gonzalez and R. E. Woods. Digital Image Processing. Addison Wesley, 2nd edition, 1992.
- . Z. Wang and D. Zhang. Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Images. IEEE Transactions on Circuits and Systems–II: Analog and Digital Signal Processing, 46(1):78 – 80, January 1999.
- . C. Butakoff and I. Aizenberg. Effective Impulse Detector Based on Rank-Order Criteria. IEEE Signal Processing Letters, 11(3):363 – 366, March 2004.
- . P. S. Windyga. Fast Impulsive Noise Removal. IEEE Transactions on Image Processing, 10(1):173 – 179, January 2001.
- . S. Haykin., Neural Networks, Ottawa.ON.Canda, Maxwell Macmillan, 1994.
- . Y.H .Pao, Adaptive Pattern Recognition and neural networks. Reading .MA addison- Wesley.1989.
- . J. Park, and I. W. Sandberg, “Universal approximation using radial basis function networks, ”Neural Comput., vol. 3, 1991,pp. 246–257.
- . J. C. Patra, R. N. Paul, B. N. Chatterji, G. Panda, Identification of nonlinear dynamic systems using functional link artificial neural networks, IEEE Trans., Systems, Man and Cybernetics, Part B, Vol.29, April 1999, pp.254-262.
- . Chebysev Functional Link Artificial Neural Networks for Denoising of Image Corrupted by Salt and Pepper Noise , ACEEE International Journal on Signal and Image Processing Vol 1, No. 1, Jan 2010.
- . Nonlinear channel equalization for wireless communication systems using Legendre neural networks Jagdish C. Patra, Pramod K.Meher, Goutam Chakraborty, Elsevier, Signal Processing 89 (2009) 2251–2262.
- . S. J. Ko and Y. H. Lee. Center Weighted Median Filters and Their Applications to Image Enhancement. IEEE Transactions on Circuits and Systems, 38(9):984 – 993, September 1991.
- . T. Chen and H. R. Wu. Adaptive Impulse Detection Using Center-Weighted Median Filters. IEEE Signal Processing Letters, 8(1):1 – 3, January 2001.
- . D. R. K. Brownrigg. The Weighted Median Filter. Communications ACM, 27:807 – 818, August 1984. 75.
- . B. I. Justusson. Median Filtering: Statistical Properties. Two-Dimensional Signal Processing-II, T. S. Hwang Ed. New York: Springer Verlag, 1981.
- . V. Crnojevic, V. Senk, and Z. Trpovski. Advanced Impulse Detection Based on Pixel-Wise MAD. IEEE Signal Processing Letters, 11(7):589 – 592, July 2004.
- . S. Zhang and Md. A. Karim. A New Impulse Detector for Switching Median Filters. IEEE Signal Processing Letters, 9(11):360 – 363, November 2002.