Call for Paper - November 2020 Edition
IJCA solicits original research papers for the November 2020 Edition. Last date of manuscript submission is October 20, 2020. Read More

Removal of Impulse Noise using First Order Neighborhood Mean Filter

Print
PDF
International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 87 - Number 4
Year of Publication: 2014
Authors:
Priyanka Shrivastava
Uday Pratap Singh
Vineet Richhariya
10.5120/15199-3585

Priyanka Shrivastava, Uday Pratap Singh and Vineet Richhariya. Article: Removal of Impulse Noise using First Order Neighborhood Mean Filter. International Journal of Computer Applications 87(4):34-39, February 2014. Full text available. BibTeX

@article{key:article,
	author = {Priyanka Shrivastava and Uday Pratap Singh and Vineet Richhariya},
	title = {Article: Removal of Impulse Noise using First Order Neighborhood Mean Filter},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {87},
	number = {4},
	pages = {34-39},
	month = {February},
	note = {Full text available}
}

Abstract

Noise removal is one of the most important parts to get original image from highly corrupted image. The image can be corrupted with noise during transmission from noisy channel, sensors or due to some environmental conditions. This makes the image visually unpleasant. Impulsive noise may occur during transmission which highly corrupts the image. In this paper an algorithm is designed to remove the impulsive noise (salt and pepper) from corrupted gray scale and color images. In past years researchers proposed many algorithms to remove the impulse noise but they fail to give better results at high noise density i. e. 80%-90%. The proposed algorithm works on two stages first stage is to detect the noisy pixel and the second stage is to replace the noisy pixel. This algorithm considers first order neighborhood pixels for detecting the noisy pixel and mean filter is used for de-noising. Color images are also de-noised by extracting the R, G and B pixels from noisy image and then they are de-noised separately and then merged together again to form the color image. All the other algorithms are compared with the proposed algorithms and found that the proposed algorithm have good noise removal capabilities at high densities. The presented algorithm shows better results than Standard Median Filter (SMF), Adaptive Median Filter (AMF), Progressive Switched Median Filter (PSMF), Decision Based Algorithm (DBA), Modified Decision Based Algorithm (MDBA), Modified Decision Based Unsymmetrical Trimmed Median Filter (MDBUTMF), and Modified Non-Linear Filter (MNF). Different grayscale and color images are tested by using the algorithm and it gave better Peak Signal Noise Ratio (PSNR) and Image Enhancement Factor (IEF) at low, medium and high noise densities.

References

  • T. A. Nodes and N. C. Gallagher, Jr. , "The output distribution of median type filters," IEEE Trans. Communication, 32(5): 532-541, 1984.
  • H. Hwang and R. A. Haddad, "Adaptive median filters: new algorithms & results," IEEE Transactions on image processing, Vol. no:4, pp. 499-502, 1995.
  • J. Astola and P. Kuosmaneen, Fundamentals of Nonlinear Digital Filtering, 1997.
  • S. Zhang and M. A. Karim, "A new impulse detector for switching median filters," IEEE signal Process. Lett. , vol. 9, no. 11, pp. 360-363, Nov. 2002.
  • Fanzhi Kong, Wenbin Ma, "A Fast adaptive Mean Filtering Algorithm,", 2nd International Conference on Industrial and Information Systems, IEEE 2010.
  • P. E. Ng and K. K. Ma, "A switching median filter with boundary discriminative noise detection for extremely corrupted images," IEEE Trans. Image Process. , vol. 15, no. 6, pp. 1506-1516, Jun 2006.
  • K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision based algorithm for removal of high-density salt and pepper noise in image," EURASIP J. Adv. Signal Process, 2010.
  • K. S. Srinivasan and D. Ebenezer, "A new fast and efficient decision based algorithm for removal of high-density impulse noises," IEEE Signal Processing Letters, vol. no:14 pp. 189-192, 2007.
  • V. Jayaraj and D. Ebenezer, "A new switching-based median filtering scheme and algorithm for removal of high-density salt and pepper noise in image," EURASIP J. Adv. Signal Process. , 2010.
  • K. S. Srinivasan, V. Jayaraj and D. Ebenezer, "A new and efficient algorithm for removal of high-density salt and pepper noise in images and videos," Second Int. Conf. Computer Modeling and Simulation, 2010, pp. 409-413.
  • S. Esakkirajan, T. Veerakumar, Adabala N. Subramanyam, and C. H. PremChand, "Removal of high Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter," IEEE Signal Processing Letters, vol. 18, no. 5, May 2011.
  • T. M. Benazir and B. M. Imran, "Removal of High and Low Density Impulse Noise From Digital Images Using Non Linear Filter," International Conference on Signal Processing, Image Processing and Pattern Recognition, [ICSIPR) 2013.