Research Article
A Histogram based Algorithm for Denoising Images Corrupted with Impulse Noise
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 71 - Issue 2 |
| Published: June 2013 |
| Authors: Jasmeen Kaur |
10.5120/12331-8591
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Jasmeen Kaur . A Histogram based Algorithm for Denoising Images Corrupted with Impulse Noise. International Journal of Computer Applications. 71, 2 (June 2013), 18-22. DOI=10.5120/12331-8591
@article{ 10.5120/12331-8591,
author = { Jasmeen Kaur },
title = { A Histogram based Algorithm for Denoising Images Corrupted with Impulse Noise },
journal = { International Journal of Computer Applications },
year = { 2013 },
volume = { 71 },
number = { 2 },
pages = { 18-22 },
doi = { 10.5120/12331-8591 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2013
%A Jasmeen Kaur
%T A Histogram based Algorithm for Denoising Images Corrupted with Impulse Noise%T
%J International Journal of Computer Applications
%V 71
%N 2
%P 18-22
%R 10.5120/12331-8591
%I Foundation of Computer Science (FCS), NY, USA
Abstract
An algorithm is designed for the histogram representation of an image, subsequent detection of Salt and Pepper (SP) noise in the image and finally the restoration of the image from this noise. The image is first represented as histogram, then fuzzy rule are applied on this. The images taken up for experimental analyses are subjected to the fuzzy based filter for SP noise removal. The proposed algorithm exhibits superiority over traditional algorithms and recently proposed ones in terms of visual quality, Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE). This superior performance of the fuzzy based Histogram Adaptive Filter is solely due to the histogram representation of the test images.
References
- J. Alex Stark, "Adaptive Image Contrast Enhancement using Generalization of Histogram Equalization", IEEE transactions on Image Processing Vol. 9, No. 5, May 2000.
- Rafael C. Gonzalez, Richard E. Woods, "Digital Image processing", 2nd edition, Prentice Hall, 2002.
- M. Abdullah-Al-Wadud, Md. Hasanul Kabir, M. Ali Akber Dewan, Oksam Chae, "A Dynamic Histogram Equalization for Image Contrast Enhancement", IEEE Transactions, Consumer Electronics, Vol. 53, No. 2, pp 593-600, May 2007.
- Russo, F. , "A new class of fuzzy operators for image processing: design and implementation", Proceedings of the Second IEEE International Conference on Fuzzy Systems, FUZZ-IEEE '93, San Francisco, March 28 - April I, pp. 815-820, 1993.
- T. Peli, J. S. Lim, "Adaptive Filtering for Image Enhancement", Optical Engineering, v01. 21, pp. 108-1 12, Jan/Feb 1982.
- Z. Chi,H. Yan,T. Pham, "Fuzzy Algorithms: with Application to Image Processing and Pattern Recognition", Advances in Fuzzy Systems- Application and Theory, Vol. 10, 1996.
- Tinku Acharya, Ajoy. K. Ray, "Image Processing–Principles andApplications", Hoboken, New Jersey, A JOHN WILEY & SONS, MC. , Publication, 2005.
- Detail information about the Peak signal to noise ratio, http://en. wikipedia. org/wiki/Peak_signal-to-noise_ratio
- Standard original images, http://www. ece. rice. edu/~wakin/images/
- Lee C. S. , Kuo Y. H. & Yu P. T. , "Weighted fuzzy mean filters for image processing", in Fuzzy Sets and Systems, Vol. 89, 1997, pp. 157-180.
- Arakawa K. , "Fuzzy rule-based image processing with optimization", in Fuzzy Techniques in Image Processing (Kerre E. E. & Nachtegael M. ,editors), Springer-Verlag, pp. 222-247, 2000.
- A. K. Jain, Fundamentals of, "Digital Image Processing". Prentice-Hall, 1989.
- C. S. Lee,Y. H,Kuo and P. T. Yu, "Weighted Fuzzy Mean Filter for Image Processing", Fuzzy Set Syst. ,no. 89, pp. 157-180,1997.
- F. Farbiz and M. B. Mehnaz, "Fuzzy Techniques in Image Processing" Springer-Velag, Vol. 52, pp. 194-221, 2000.
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