African Journal of Mathematics and Computer Science Research
Subscribe to AJMCSR
Full Name*
Email Address*

Article Number - F48115D41439


Vol.6(9), pp. 177-182 , October 2013
DOI: 10.5897/AJMCSR11.124
ISSN: 2006-9731



Full Length Research Paper

Hybrid filters for medical image reconstruction



S. Vijaya Kumar
  • S. Vijaya Kumar
  • Department of IT, RGM College of Engineering and Technology, Nadyal-518501, India
  • Google Scholar







 Accepted: 11 September 2011  Published: 31 October 2013

Copyright © 2013 Author(s) retain the copyright of this article.
This article is published under the terms of the Creative Commons Attribution License 4.0


The most significant feature of diagnostic medical images is to reduce Gaussian noise, and salt and pepper noise which is commonly found in medical images and make better image quality. In recent years, technological development has significantly improved analyzing medical imaging. This paper proposes different hybrid filtering techniques for the removal of Gaussian noise, and salt and pepper noise. The filters are treated in terms of a finite set of certain estimation and neighborhood building operations. A set of such operations is suggested on the base of the analysis of a wide variety of nonlinear filters described in the literature.

Key words: Gaussian noise, salt and pepper noise, hybrid filter.

Gnanambal I, Marudhachalam R (2011). New Hybrid Filtering Techniques for Removal of Gaussian Noise from Medical Images: ARPN. J. Eng. Appl. Sci. pp. 08-12.
 
Gonzalez R, Woods R (1992). Digital Image Processing. Adison -Wesley, New York.
 
Hakan GS, Richard AP, Benoit D (2002). Topological Median Filter: IEEE . Image Process. 11(2):89-104.
http://dx.doi.org/10.1109/83.982817
PMid:18244615
 
Hu H, de Haan G (2006). Classification-based hybrid filters for image processing: Proc. SPIE, Visual Communications and Image Processing. 6077, 607711.1-607711.10.
 
Ioannis P, Anastasias NV (1990). Nonlinear Digital Filters: Principles and Applications. NJ: Springer Publisher.
 
Klaus R, Rolf U (1992). An Adaptive Recursive 2-D Filter for Removal of Gaussian Noise in Images: IEEE Trans. Image Process 431-436.
 
Mamta J, Rajni M (2009). An Improved Adaptive Median Filtering Method for Impulse Noise Detection. Int. J. Recent Trends Eng. 1(1):274-278.
 
Peng S, Lucke L (1995). A hybrid filter for image enhancement:Proc. of International Conference on Image Processing (ICIP). 1:163-166.
 
Salem SA, Kalyankar NV, Khamitkar SD (2010). A Comparative Study of Removal Noise from Remote Sensing Image: Int. J. Comp. Sci. 7(1):32-36.
 
Sivakumar R (2007). Denoising of Computer Tomography images using curvelet transform: ARPN J. Eng. Appl. Sci. 2(1):21-26.
 
Turkey JW (1974). Nonlinear (nonsuperposable) methods for smoothing data: Proc. Congr. Rec. EASCOM '74. pp. 673-681.
 
Yanchun W, Dequn L, Heng M, Yan W (2006). An Algorithm for Image Denoising Based on Mixed Filter: Proceedings of the 6th World Congress on Intelligent Control and Automation. pp. 690-9693.

 


APA (2013). Hybrid filters for medical image reconstruction. African Journal of Mathematics and Computer Science Research, 6(9), 177-182.
Chicago S. Vijaya Kumar. "Hybrid filters for medical image reconstruction." African Journal of Mathematics and Computer Science Research 6, no. 9 (2013): 177-182.
MLA S. Vijaya Kumar. "Hybrid filters for medical image reconstruction." African Journal of Mathematics and Computer Science Research 6.9 (2013): 177-182.
   
DOI 10.5897/AJMCSR11.124
URL http://academicjournals.org/journal/AJMCSR/article-abstract/F48115D41439

Subscription Form