A Hybrid Technique for De-Noising Multi-Modality Medical Images by Employing Cuckoo’s Search with Curvelet Transform

  • Qaisar Javaid Department of Computer Science and Software Engineering, International Islamic University, Islamabad.
  • Muhammad Arif Department of Computer Science, University of Gujrat, Gujrat
  • Munam Ali Shah Department of Computer Science, COMSATS Institute of Information Technology, Islamabad
  • Muhammad Nadeem Department of Computer Science and Software Engineering, International Islamic University, Islamabad.

Abstract

De-noising of the medical images is very difficult task. To improve the overall visual representation we need to apply a contrast enhancement techniques, this representation provide the physicians and clinicians a good and recovered diagnosis results. Various de-noising and contrast enhancements methods are develops. However, some of the methods are not good in providing the better results with accuracy and efficiency. In our paper we de-noise and enhance the medical images without any loss of information. We uses the curvelet transform in combination with ridglet transform along with CS (Cuckoo Search) algorithm. The curvlet transform adapt and represents the sparse pixel informations with all edges. The edges play very important role in understanding of the images. Curvlet transform computes the edges very efficiently where the wavelets are failed. We used the CS to optimize the de-noising coefficients without loss of structural and morphological information. Our designed method would be accurate and efficient in de-noising the medical images. Our method attempts to remove the multiplicative and additive noises. Our proposed method is proved to be an efficient and reliable in removing all kind of noises from the medical images. Result indicates that our proposed approach is better than other approaches in removing impulse, Gaussian, and speckle noises.

Published
Jan 1, 2018
How to Cite
JAVAID, Qaisar et al. A Hybrid Technique for De-Noising Multi-Modality Medical Images by Employing Cuckoo’s Search with Curvelet Transform. Mehran University Research Journal of Engineering and Technology, [S.l.], v. 37, n. 1, jan. 2018. ISSN 2413-7219. Available at: <http://publications.muet.edu.pk/index.php/muetrj/article/view/94>. Date accessed: 21 june 2018. doi: http://dx.doi.org/10.22581/muet1982.1801.03.
This is an open Acess Article published by Mehran University of Engineering and Technolgy, Jamshoro under CCBY 4.0 International License