Abstract
This paper focuses on the removal of salt and pepper noise from a contaminated image. A Probabilistic Decision Based Improved Trimmed Median Filter (PDITMF) is proposed here. The proposed PDITMF algorithm resolves the conflict regarding an even number of noise free pixel of Trimmed Median Filter. The proposed algorithm makes use of two estimation techniques for de-noising, namely, Improved Trimmed Median Filter (ITMF), and Patch Else Improved Trimmed Median Filter (PEITMF) depending upon noise density. The algorithm experiments with many standard sample images. Simulation results show the proposed algorithm is capable of de-noising the image very efficiently. The algorithm has a better visual representation and it outperforms the existing well-known algorithms in context to peak signal-to-noise ratio (PSNR) as well as image enhancement factor (IEF) with lower execution time (ET) at all noise densities.
Similar content being viewed by others
REFERENCES
V. B. S. Prasath, “Image denoising by anisotropic diffusion with inter-scale information fusion,” Pattern Recogn. Image Anal. 27 (4), 748–753 (2017).
V. Kober, M. Mozerov, J. Álvarez-Borrego, and I. A. Ovseyevich, “Algorithms for impulse noise removal from corrupted color images,” Pattern Recogn. Image Anal. 17 (1), 125–130 (2007).
R. C. Gonzalez and R. E. Woods, Digital Image Processing, 2nd ed. (Prentice-Hall, Upper Saddle River, NJ, 2002).
A. D. Poularikas, “Nonlinear Digital Filtering,” Chapter 41 in Handbook of Formulas and Tables for Signal Processing (CRC Press, Boca Raton, FL, 1999).
H. Hwang and R. A. Haddad, “Adaptive median filters: new algorithms and results,” IEEE Trans. Image Process. 4 (4), 499–502 (1995).
S. Zhang and M. A. Karim, “A new impulse detector for switching median filters,” IEEE Signal Process. Lett. 9 (11), 360–363 (2002).
S. Akkoul, R. Lédée, R. Leconge, and R. Harba, “A new adaptive switching median filter,” IEEE Signal Process. Lett. 17 (6), 587–590 (2010).
W. Luo, “An efficient detail-preserving approach for removing impulse noise in images,” IEEE Signal Process. Lett. 13 (7), 413–416 (2006).
S. Esakkirajan, T Veerakumar, A. N. Subramanyam, and C. H. PremChand, “Removal of high density salt and pepper noise through modified decision based unsymmetric trimmed median filter,” IEEE Signal Process. Lett. 18 (5), 287–290 (2011).
G. Balasubramanian, A. Chilambuchelvan, S. Vijayan, and G. Gowrison, “Probabilistic decision based filter to remove impulse noise using patch else trimmed median,” AEUE–Int. J. Electron. Commun. 70 (4), 471–481 (2016).
K. S. Srinivasan and D. Ebenezer, “A new fast and efficient decision-based algorithm for removal of high-density impulse noises,” IEEE Signal Process. Lett. 14 (3), 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 images,” EURASIP J. Adv. Signal Process. 2010, Article 690218 (2010).
U. Erkan and L. Gökrem, “A new method based on pixel density in salt and pepper noise removal,” Turk. J. Electr. Eng. Comput. Sci. 26 (1), 162–171 (2018).
S. Beagum, S. Fareed, and S. S. Khader, “Fast adaptive and selective mean filter for the removal of high-density salt and pepper noise,” IET Image Process. 12 (8), 1378–1387 (2018).
J. Chen, Y. Zhan, H. Cao, and X. Wu, “Adaptive probability filter for removing salt and pepper noises,” IET Image Process. 12 (6), 863–871 (2018).
A. K. Samantaray, P. Kanungo, and B. Mohanty, “Neighbourhood decision based impulse noise filter,” IET Image Process. 12 (7), 1222–1227 (2018).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
The authors declare that they have no conflicts of interest.
Additional information
Amit Prakash Sen received his B.Tech degree in Electronics and Telecommunication Engineering from Biju Patnaik University of Technology, Rourkela and M.Tech degree in Electronics and Communication Engineering from West Bengal University of Technology, Kolkata. He has eight years of teaching experience as an Asst. Professor. Presently, he is working as a Research Scholar in School of Electronics Engineering, KIIT University, Bhubaneswar, India. His field of research is image processing, machine learning, and VLSI.
Nirmal Kumar Rout is presently working as a Professor, School of Electronics Engineering, KIIT University, Bhubaneswar, India. He received B.E. degree in Electronics and Telecommunication Engineering from University College of Engineering, Sambalpur University, in 1991, M.Tech degree in Computer Science from Utkal University, in 2001, and PhD degree in Electronics and Telecommunication Engineering from KIIT University, in 2014. He has published a number of research papers in various refereed international journals and conferences. His current research interest includes active noise control, adaptive signal processing, image processing soft computing and evolutionary computing.
Rights and permissions
About this article
Cite this article
Sen, A.P., Rout, N.K. Probabilistic Decision Based Improved Trimmed Median Filter to Remove High-Density Salt and Pepper Noise. Pattern Recognit. Image Anal. 30, 401–415 (2020). https://doi.org/10.1134/S1054661820030244
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S1054661820030244