Application of Bacterial Foraging Optimisation as a De - noising filter

Suman Yaduwanshi; Jagroop Singh Sidhu

doi:https://doi.org/10.14445/22315381/IJETT-V4I7P154

Research Article | Open Access | Download PDF

Volume 4 | Issue 7 | Year 2013 | Article Id. IJETT-V4I7P154 | DOI : https://doi.org/10.14445/22315381/IJETT-V4I7P154

Application of Bacterial Foraging Optimisation as a De - noising filter

Suman Yaduwanshi , Jagroop Singh Sidhu

Citation :

Suman Yaduwanshi , Jagroop Singh Sidhu, "Application of Bacterial Foraging Optimisation as a De - noising filter," International Journal of Engineering Trends and Technology (IJETT), vol. 4, no. 7, pp. 3049-3055, 2013. Crossref, https://doi.org/10.14445/22315381/IJETT-V4I7P154

Abstract

De - noising of image still a concerned for researchers working in this area. It is further challenging in case of medical images mainly images of the internal organs. Various digital filters have been developed and tried by researchers to provide ideal solutio n in the de - noising of medical images. In the present paper the authors present a Soft Computing approach to de - noise the medical images. Bacterial Foraging Optimisation which is a bio - inspired algorithm is used as filter to de - noise medical images like CT - Scan and MRI of pancreas. The performance metrics like MSE and PSNR are calculated which show that Bacterial Foraging Optimisation can act as potential tool for de - noising images.

Keywords

BFO, cost function, MSE, PSNR, De-noising, Medical image

References

[1] Choubey, Abha, Sinha, G. R., Choubey, Siddharth; "A Hybrid filtering Technique in Medical Image denoising Blending of Neural Network and Fuzzy Inference." ICECT Vol.1, pp. 170 - 177, April 2011
[2] Daiyan, G.M., Mottalib, M.A.; "Removal of high de nsity Salt and Pepper noise through modified median filter." International Conference on Informatics, Electronoics and vision, pp. 565 - 570, 2012
[3] Gonzalez,Rafel C. and Woods, Richard E.; "Digital Image Processing." Second edition, Publising House of Electro nics Industry, Beijing, 2003
[4] Kennedy,J and Eberhart, R.C; "Particle Swarm Optimisation." Proceedings of IEEE International C onference on Neural Network, , 1995 Piscataway, NJ, pp.1942 - 1948
[5] Kneey Kal Vin Toh and Nor Ashidi Mat Isa; "Noise Adaptive Fuzzy Switching Median filter for Salt & Pepper Noise Reduction." IEEE Signal Processing Letters, Vol. 17, No. 3, pp. 281 - 284 , March 2010
[6] Lu Zhang, Jiaming Chen, Yuein Zhu, Zianhua Luo; "Comparisions of several New Denoising Methods for Medical Images." Intern ational Conference on Bioinfomatics and Biomedical Engineering, June 2009 , pp. 1 - 4,
[7] Newton, T.H. and Potts, D.G.; "Technical Aspects of Computed Tomography in Radiology of skull and Brain." Vol.5 ISBN - 0 - 8016 - 3662 - 0, pp. 3941 - 3956, 1981
[8] Passino, K.M.; "Bio mimicry of Bacterial Foraging for Distributed Optimisation and Control." IEEE Control and System Magzene, pp. 52 - 67, June 2002
[9] Pattnaik, S.S; Backwad, K.M.; Sohi, B.S.; Ratho, R.K.; S.Devi; "Swine Influenza Model Based Optimisation (SIMBO)." Applied Soft C omputing, Vol.1, pp.18 - 30, Sept. 2012
[10] Zhou Wang David Zhang; "Progressive Switching Median filter for the removal of Impulse Noise from Highly corrupted Images." IEEE Transaction on Circuits and System – II: Analog and Digital Processing, Vol.46,No.1 pp. 78 - 80 Jan 1999
[11] Zhu Youlin; Huang Cheng; "Image denoising algorithm based on PSO Optimising Structuring element." Control and Decision C onference, , 2012 , pp.2404 - 2408
[12] Saeid Fazli, H. Bouzari and H.M. Pour ?Complex PDE Image Denoising Based on Particle Swarm Optimization?,International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, pp. 364 - 370, Oct - 2010