Removal of Fix Magnitude Impulsive Noise (FMIN) Through Innovative Recursive MDBUTMF Procedure
Main Article Content
Abstract
This article proposes an innovative recursive modied decision based unsymmetrical trimmed median filter (RMDBUTMF) procedure for noisy overriding of digital photographs, which are eminently contaminated by FMIN. The proposed procedure reinstates the noisy photographical basis (which has magnitude at 0 or 255) by trimmed median magnitude (or the mean magnitude of all the free-noise photographical basis) in the computational photographical basis region under the recursive framework. The proposed procedure is experimented on distinctive digital photographs (Lena, Girl, Pepper and F16) on broad noise density and the proposed procedure reveals superior noisy-overridden photographs than the Mean Filter (MF), Median Filter (SMF), Adaptive Median Filter (AMF), Weight Median Filter (WMF), MDBUTMF in both Peak Signal-to-Noise Ratio (PSNR) and photographical quality.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice-Hall,Upper Saddle
River,NJ, USA, 2nd edition, 2002.
A. S. M. Shafi, et.al, “Decomposition of color wavelet with higher order statistical texture and convolutional neural network features set based classification of colorectal polyps from video endoscopy,” International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 3, pp. 2986-2996, Jun. 2020.
S. Bagchi, et.al, “Image processing and machine learning techniques used in computer-aided detection system for mammogram screening-A review,” International Journal of Electrical and Computer Engineering (IJECE), vol. 10, no. 3, pp. 2336-2348, Jun. 2020.
N. D. Abdullah, et.al, “Analysis of texture features for wood defect classification,” Bulletin of Removal of Fix Magnitude Impulsive Noise (FMIN) Through Innovative Recursive MDBUTMF Procedure Electrical Engineering and Informatics, vol. 9, no. 1, Feb. 2020.
A. J. Qasim, et.al, “Review on techniques and file formats of image compression,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 2, Apr. 2020.
S. P. Ramalingam, R. K. Nadesh and N. C. SenthilKumar, “Robust Face Recognition Using Enhanced Local Binary Pattern,” Bulletin of Electrical Engineering and Informatics, vol. 7, no. 1, Mar. 2018.
V. H. Patil, G. K. Kharate and K. S. Mohan, “Super Resolution Imaging Needs Better Registration for Better Quality Results,” Bulletin of Electrical Engineering and Informatics, vol.1, no.1, Mar. 2012.
C. Deng, et.al, “Image Super-Resolution Reconstruction Based On L1/2 Sparsity,” Bulletin of Electrical Engineering and Informatics, vol. 3, no. 3, Sep. 2014.
D. Kesrarat, et.al, “A Novel Elementary Spatial Expanding Scheme Form on SISR Method
with Modifying Geman&Mcclure Function,” TELKOMNIKA Telecommunication, Computing, Electronics and Control, Indonesia, vol.17, no.5, Oct 2019.
W. K. Pratt, “Median filtering,” Tech. Rep., Image Proc. Inst., Univ. Southern California, Los Angeles, Sep. 1975.
J. Astola, P. Haavisto and Y. Neuvo, “Vector median filters,” in Proceedings of the IEEE, vol. 78, no. 4, pp. 678-689, Apr. 1990.
H. Hwang and R. A. Haddad, “Adaptive median filters: new algorithms and results,” in IEEE Transactions on Image Processing, vol. 4, no. 4, pp. 499-502, Apr. 1995.
O. P. V. and N. Sharma, “Intensity Preserving Cast Removal in Color Images Using Particle Swarm Optimization,” International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2581 – 2595, Oct. 2017.
M. Hamiane and F. Saeed, “SVM Classification of MRI Brain Images for Computer-Assisted Diagnosis,” International Journal of Electrical and Computer Engineering (IJECE), vol. 7, no. 5, pp. 2555-2564, , Oct. 2017.
A. Khmag, S. Ghoul, S. A. R. Al-Haddad and N. Kamarudin, “Noise Level Estimation for Digital Images Using Local Statistics and Its Applications to Noise Removal,” TELKOMNIKA
Telecommunication, Computing, Electronics and Control, Indonesia, vol.16, no.2, Apr. 2018.
K. Arun Sai and K. Ravi, “An Efficient Filtering Technique for Denoising Colour Images,” International Journal of Electrical and Computer Engineering (IJECE), vol. 8, no. 5, pp. 3604-3608, Oct. 2018.
Z. M. Ramadan, “Effect of kernel size on Wiener 501 and Gaussian image filtering,” TELKOMNIKA Telecommunication, Computing, Electronics and Control, Indonesia, vol.17, no.3, Jun. 2019
J. Na‘am, et.al, “Filter technique of medical image on multiple morphological gradient
(MMG) method,” TELKOMNIKA Telecommunication, Computing, Electronics and Control,
vol.17, no.3, Jun. 2019.
B. Charmouti, et.al, “An overview of the fundamental approaches that yield several image denoising techniques,” TELKOMNIKA Telecommunication, Computing, Electronics and Control, Indonesia, vol.17, no.6, Dec. 2019.
L. Abderrahim, et.al, “Novel design of a fractional wavelet and its application to image denoising,” Bulletin of Electrical Engineering and Informatics, vol. 9, no. 1, Feb. 2020.
Y. Y. Al-Aboosi, et.al, “Image denosing in underwater acoustic noise using discrete wavelet transform with different noise level estimation,” TELKOMNIKA Telecommunication, Computing, Electronics and Control, Indonesia, vol. 18, no. 3, Jun. 2020.
S. Rajkumar and G. Malathi, “An Efficient Image Denoising Approach for the Recovery of Impulse Noise,” Bulletin of Electrical Engineering and Informatics, vol. 6, no. 3, Sep. 2017.
V. Patanavijit, “Denoising Performance Analysis of Adaptive Decision Based Inverse Distance Weighted Interpolation (DBIDWI) Algorithm for Salt and Pepper Noise,” International Journal of Electrical and Computer Engineering (IJECE), Indonesia, Aug. 2019.
V. Kishorebabu, G. Packyanathan, H. Kamatham and V. Shankar , “An adaptive decision based interpolation scheme for the removal of high density salt and pepper noise in images,” EURASIP Journal on Image and Video Processing, vol. 2017, no. 67, Sep. 2017.
V. Patanavijit, et.al, “The Statistical Analysis of Random-Valued Impulse Noise Detection Techniques Based on The Local Image Characteristic: ROAD, ROLD and RORD,” International Journal of Electrical and Computer Engineering (IJECE), Indonesia, Aug. 2019.
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,” in IEEE Signal Processing Letters, vol. 18, no. 5, pp. 287-290, May 2011.
V. Patanavijit, et.al., “An Innovate Noise Extinguish Technique Ground on Iterative Median Filter for Low-Density Fix-Valued Impulse Noise,” The National Conference on Information Technology 2022 (NCIT 2022), Nov. 2022.