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Performance Comparison of Various Image Denoising Filters under Spatial Domain

International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 96 - Number 19
Year of Publication: 2014
Inderpreet Singh
Nirvair Neeru

Inderpreet Singh and Nirvair Neeru. Article: Performance Comparison of Various Image Denoising Filters under Spatial Domain. International Journal of Computer Applications 96(19):21-30, June 2014. Full text available. BibTeX

	author = {Inderpreet Singh and Nirvair Neeru},
	title = {Article: Performance Comparison of Various Image Denoising Filters under Spatial Domain},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {96},
	number = {19},
	pages = {21-30},
	month = {June},
	note = {Full text available}


Image denoising is very important during enhancement of image. Original Image is generally corrupted with various types of noise. The noise present in the images may appear as additive or multiplicative components. The most challenging problem is removing that noise from an Image while preserving its details. Several noise removal techniques have been developed so far each having its own advantages and disadvantages. The focus of this paper is to study various spatial filters and to compare their performance in removing different types of noise. Here quantitative measure of comparison is provided by the Peak Signal to Noise Ratio (PSNR) parameter.


  • A. Bovik, Handbook of Image and Video Processing. New York: Academic, 2000.
  • C. S. Lee, S. M. Guo, and C. Y. Hsu, "Genetic-based fuzzy image filter and its application to image processing," IEEE Trans. Syst. Man Cybern. B, bern. , vol. 35, no. 4, pp. 694–711, Aug. 2005.
  • Gaussian Noise [Online]. Available: https://www. cs. auckland. ac. nz/courses/Gaussian%20Filtering_1up. pdf
  • Gaussian noise [Online]. Available: http://en. wikipedia. org/wiki/ Gaussian_noise
  • J. Harikiran, B. Saichandana and B. Divakar, "Impulse Noise Removal in Digital Image. " International Journal of Computer Applications, Vol. 10, no 8, pp. 39-42.
  • J. H. Hong, S. B. Cho, and U. K. Cho, "A novel evolutionary approach to image enhancement filter design: method and applications," IEEE Trans. Syst. Man Cybern. B, bern. , vol. 39, no. 6, pp. 1446–1457, Dec. 2009.
  • J. H. Wang, W. J. Liu, and L. D. Lin, "Histogram-based fuzzy filter for image restoration," IEEE Trans. Syst. Man Cybern. B, bern. , vol. 32, no. 2, pp. 230–238, Apr. 2002.
  • Keyur Patel and Hardik N. Mewada, "A Review on Different Image De-noising Methods", International Journal on Recent and Innovation Trends in Computing and Communication, Vol 2 Issue 1, 155-159 March 2014
  • Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian, "Image denoising with block-matching and 3D filtering" Image Processing: Algorithms and Systems, SPIE ,Electronic Imaging,Vol. 6064,2006.
  • K. Somasundaram and P. Kalavathi, "Medical Image Denoising using Non-Linear Spatial Mean Filters for Edge Detection. ", rural. univ. ac. in, pp. 149-153
  • K. S. Srinivasan, D. Ebenezer, "A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises", IEEE Signal Processing Letters, Vol. 14, No. 3, March 2007.
  • Li Dan, Wang Yan and Fang Ting "Wavelet Image Denoising Algorithm based on Local Adaptive weiner filtering," International Conference on Mechatronic Science, Electrical Engineering and Computer August 19-22, Jilin, China 2011.
  • Ling Shao, Ruomei Yan and Xuelong Li, "From Heuristic Optimization to Dictionary Learning: A Review and Comprehensive Comparison of Image Denoising Algorithms," IEEE Transactions on Cybernetics, 1-14 August, 2013.
  • Mehmet Sezgin and Bu¨ lent Sankur, "Survey on Image Thresholding Technique and quantitative performance evaluation", Journal of Electronic Imaging 13(1), 146–165 January 2004.
  • Mr. Amit Agrawal, Ramesh Raskar, "Optimal single image capture for motion deblurring", IEEE Conference on Computer Vision and Pattern Recognition, pages 2560-2567, 2009.
  • Mr. Pawan Patidar and et al. Image De-noising by Various Filters for Different Noise in International Journal of Computer Applications (0975 – 8887) Volume 9– No. 4, November 2010
  • Mukesh C. Motwani, Mukesh C. Gadiya and Rakhi C. Motwani, "Survey of Image Denoising Techniques. ," Proc. of GSPx, Santa Clara Convention Center, Santa Clara, CA, pp. 27-30, 2004.
  • Priyanka Kamboj and Varsha Rani, "A Brief Study of Various Noise Model and filtering Techniques," Journal of Global Research in Computer Science, Volume 4, No 4, pp. 166-171 , April 2013.
  • R. C. Gonzalez and R. E. Woods, "Digital Image Processing," second ed. , Prentice Hall, Englewood, Englewood, Cliffs, NJ, 2002.
  • Speckle noise [Online]. Available: http://en. wikipedia. org/wiki/ Speckle_noise