Optimized connected Median filter using Particle Swarm Optimization

Authors(2) :-M. Rajalakshmi, Dr. P. Subashini

In the image processing Median filter were used to remove the impulse noise. It preserves the edges for the next level operations such as segmentation and object recognition. The present paper deals with the preprocessing of chili x-ray images. The researcher has already preprocessed the chili x-ray images by adopting the Average filter, Median filter, Wiener filter, Gamma intensity correction, CLAHE, 4-connected Median filter and weighted 4-connected median filter. The result of the above stated preprocess methods to contain noise in the pixels, hence it is considered as unsuitable for next level operations. To remove such noise from the image, this paper contributes a precise and well-organized algorithm. The proposed noise removal algorithm replaces the noisy pixels by using '4-connected median value' and replaces the remaining pixels by using 'weighted 4-connected median value' in the selected window. The replacement of middle pixel value in 4-connected median filter is done through particle swarm optimization algorithm. Peak Signal to Noise Ratio used as the fitness function in the particle swarm optimization algorithm. The performance measures were taken for all the noise removal algorithm. Among the various results obtained, the proposed algorithm works better than others.

Authors and Affiliations

M. Rajalakshmi
Department of Computer Science, Avinashilingam Institute for Women, Coimbatore, India
Dr. P. Subashini
Department of Computer Science, Avinashilingam Institute for Women, Coimbatore, India

chili x-ray image, impulse noise, particle swarm optimization, weighted and 4-connected median filter, Optimized connected Median filter, Particle Swarm Optimization, Peak Signal to Noise Ratio.

  1. Amera Abdul,Wohid Funjan AL.Tayee, “Denoising An Image Based On Particle Swarm Optimization (PSO) Algorithm”, Journal of Babylon University/Pure and Applied Sciences/ No.(5)/ Vol.(21): 2013,pp.1511-1518.
  2. Anuradha, Mr.Sanjay Yadav, “ Review On:-Face Recognition algorithm based on Surf Feature Extraction, Median Filter with Particle Swarm Optimization Algorithm”,International Journal of Research Development and Innovation (IJRDI), Volume 1, Issue 2, March 2015, pp. 72-76.
  3. Baladhandapani Arunadevi, and Subramaniam N. Deepa, ”Brain Tumor Tissue Categorization In 3d Magnetic Resonance Images Using Improved PSO for Extreme Learning Machine”, Progress In Electromagnetics Research B, Vol. 49, 2013,pp. 31-54.
  4. Bharathi P. T, Dr. P. Subashini, ”Decision Based Median Filter using Particle Swarm Optimization for Impulsive Noise”, International Journal of Emerging Technologies in Computational and Applied Sciences (IJETCAS), 4(1), March-May 2013, pp.109-115.
  5. Christo Ananth, Vivek.T, Selvakumar.S., Sakthi Kannan.S., Sankara Narayanan.D, “ Impulse Noise Removal using Improved Particle Swarm Optimization”, International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) Volume 3, Issue 4, April 2014, pp. 366-370.
  6. J. K. Mandal, Somnath Mukhopadhyay, “Image Filtering using all Neighbor Directional Weighted Pixels: Optimization using Particle Swarm Optimization”, Signal & Image Processing : An International Journal (SIPIJ) Vol.2, No.4, December 2011.
  7. Jansi S., Subashini P., “Particle Swarm Optimization Based Total Variation Filter for Image Denoising”, Journal Of Theoretical And Applied Information Technology, Vol. 57 No.2, 20th November 2013.pp. 169-173.
  8. Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”, pp.40-42,191-195.
  9. Rutuja N. Kulkarni, P.C. Bhaskar, “Decision Based Median Filter algorithm using Resource Optimized FPGA to Extract Impulse Noise”, International Journal of Reconfigurable and Embedded Systems (IJRES), Vol. 3, No. 1, March 2014, pp. 1-10.
  10. Sachin K. Ingale and Ashish B. Jirapure, ”A Survey of Image Processing Technique For Contrast Improvement of An Image“, International Conference on Electronics and Communication Engineering, April 28th-29th, 2012,pp.109-114.
  11. Sarah B. Aziz and Maytham A. Shahed,”Impulsive and Poisson Noises Removal Using Takagi Neuro-Fuzzy Network”, Scientific Journal of King Faisal University (Basic and Applied Sciences),Vol.11 No.1, 2010, pp.117-141.
  12. S. Mohamed Mansoor Roomi, P.L. Muthu Karuppi, P. Rajesh and B. Guru Revathi,” A Particle Swarm Optimization Based Edge Preserving Impulse Noise Filter”, Journal of Computer Science 6 (9), 2010, pp. 1014-1020.
  13. Somnath Mukhopadhyay, J. K. Mandal,” Algorithms for Denoising Medical and Digital Images”, Elsevier, January 25, 2014, pp.1-11.
  14. Sumathi Poobal,G.Ravindran,”The Performance of Fractal Image Compression on Different Imaging Modalities Using Objective Quality Measures”, International journal of Engineering science and technology (IJEST), Vol 3. No.1 Jan 2011, pp.525-530.
  15. Suresh Kumar, Papendra Kumar, Manoj Gupta, Ashok Kumar Nagawat,”Performance Comparison of Median and Wiener Filter in Image De-noising”,International Journal of Computer Applications (0975 – 8887) Volume 12– No.4, November 2010,pp. 27-31.
  16. V.Mythili, Dr. R. Manavalan, “ Optimizing Structuring Element Using Eagle Optimization for Image Denoising: Performance Analysis”, IJASCSE, Volume 2, Special Issue 2, 2013, pp.24-30.
  17. Y.Sravani, D.Yugandhar, S.K.Nayak, “ Performance Analysis of Block PSO for Image De-noising using Wavelet Transform”, IOSR Journal of Electronics and Communication Engineering (IOSR-JECE), Vol. 9, Issue 6, Ver. II (Nov - Dec. 2014), pp. 32-37

Publication Details

Published in : Volume 2 | Issue 5 | September-October 2017
Date of Publication : 2017-10-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 19-26
Manuscript Number : CSEIT172493
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

M. Rajalakshmi, Dr. P. Subashini , "Optimized connected Median filter using Particle Swarm Optimization", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 5, pp.19-26, September-October-2017. |          | BibTeX | RIS | CSV

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