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Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application

A. Ramya1 , D. Murugan2 , T. Ganesh Kumar3 , S. Vijaya Kumar4

Section:Research Paper, Product Type: Journal Paper
Volume-06 , Issue-04 , Page no. 1-7, May-2018

Online published on May 31, 2018

Copyright © A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar , “Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application,” International Journal of Computer Sciences and Engineering, Vol.06, Issue.04, pp.1-7, 2018.

MLA Style Citation: A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar "Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application." International Journal of Computer Sciences and Engineering 06.04 (2018): 1-7.

APA Style Citation: A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar , (2018). Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application. International Journal of Computer Sciences and Engineering, 06(04), 1-7.

BibTex Style Citation:
@article{Ramya_2018,
author = {A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar },
title = {Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {06},
Issue = {04},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {1-7},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=349},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=349
TI - Adaptive Switching De-noising Filter Cascaded with Cuckoo Search Algorithm to Minimize the Mean Error – Medical Image Application
T2 - International Journal of Computer Sciences and Engineering
AU - A. Ramya, D. Murugan , T. Ganesh Kumar, S. Vijaya Kumar
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 1-7
IS - 04
VL - 06
SN - 2347-2693
ER -

           

Abstract

This paper presented the new work to minimize the mean absolute error of mammogram breast image which is highly corrupted by impulse noise density. The proposed methodology is implemented with the Adaptive Switching Weighted Median (ASWM) Filter cascaded with Cuckoo Search (CS) optimization algorithm. The efficient adaptive filter de-noises the medical image by detecting the corrupted pixel and replaces them with the median value. The CS algorithm minimizes the error rate between the ASWM filter image and corrupted image. It minimizes the Mean Absolute Error (MAE) percentage and also maximizes the Peak Signal to Noise Ratio (PSNR). This method removes the highly corrupted impulse noise of 90%. The experimental analysis is made and it is observed from the result that the proposed method is far superior to the other conventional techniques in terms of qualitative and quantitative factors. In terms of visual quality, it yields a well sharp edge region and better visual perception of the image quality.

Key-Words / Index Term

Switching filter, image de-noising, impulse noise, optimization technique, Cuckoo search algorithm

References

[1] Ramya, A., Murugan, V. and Murugan, D., 2017. Non-Linear Directive Contrast Filter for Mammogram Images to Enhance Pleomorphic Calcification. International Journal of Computer Applications, 163(7).
[2] Bhandari, A.K., Kumar, D., Kumar, A. and Singh, G.K., 2016. Optimal sub-band adaptive thresholding based edge preserved satellite image denoising using adaptive differential evolution algorithm. Neurocomputing, 174, pp.698-721.
[3] Javaid, Q., Arif, M., Shah, M.A. and Nadeem, M., 2018. A hybrid technique for De-Noising multi-modality medical images by employing cuckoo`s search with curvelet transform. Mehran University Research Journal Of Engineering & Technology, 37(1), p.29.
[4] Borra, S.R., Reddy, G.J. and Reddy, E.S., 2016. An efficient fingerprint enhancement technique using wave atom transform and mcs algorithm. Procedia Computer Science, 89, pp.785-793.
[5] Faragallah, O.S. and Ibrahem, H.M., 2016. Adaptive switching weighted median filter framework for suppressing salt-and-pepper noise. AEU-International Journal of Electronics and Communications, 70(8), pp.1034-1040.
[6] Yang, X.S. and Deb, S., 2009, December. Cuckoo search via Lévy flights. In Nature & Biologically Inspired Computing, 2009. NaBIC 2009. World Congress on (pp. 210-214). IEEE.
[7] Yang, X.S., 2014. Nature-inspired optimization algorithms. Elsevier.
[8] Mareli, M. and Twala, B., 2017. An adaptive Cuckoo search algorithm for optimisation. Applied Computing and Informatics.
[9] Ye, Z., Wang, M., Hu, Z. and Liu, W., 2015. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm. Computational intelligence and neuroscience, 2015, p.13.
[10] Babu, R.K. and Sunitha, K.V.N., 2015. Enhancing digital images through cuckoo search algorithm in combination with morphological operation. Journal of Computer Science, 11(1), p.7.
[11] Ashour, A.S., Samanta, S., Dey, N., Kausar, N., Abdessalemkaraa, W.B. and Hassanien, A.E., 2015. Computed tomography image enhancement using cuckoo search: a log transform based approach. Journal of Signal and Information Processing, 6(03), p.244.
[12] Wang, Z. and Zhang, D., 1999. Progressive switching median filter for the removal of impulse noise from highly corrupted images. IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 46(1), pp.78-80.
[13] Srinivasan, K.S. and Ebenezer, D., 2007. A new fast and efficient decision-based algorithm for removal of high-density impulse noises. IEEE signal processing letters, 14(3), pp.189-192.
[14] Meher, S.K. and Singhawat, B., 2014. An improved recursive and adaptive median filter for high density impulse noise. AEU-International Journal of Electronics and Communications, 68(12), pp.1173-1179.
[15] Nair, M.S. and Mol, P.A., 2013. Direction based adaptive weighted switching median filter for removing high density impulse noise. Computers & Electrical Engineering, 39(2), pp.663-689.
[16] Gupta, V., Chaurasia, V. and Shandilya, M., 2015. Random-valued impulse noise removal using adaptive dual threshold median filter. Journal of visual communication and image representation, 26, pp.296-304.
[17] Gandomi, A.H., Yang, X.S. and Alavi, A.H., 2013. Cuckoo search algorithm: a metaheuristic approach to solve structural optimization problems. Engineering with computers, 29(1), pp.17-35.