Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(1.91MB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Selective Median Switching Filter for Noise Suppression in Microstructure Images of Material
P.S. Hiremath, Anita Sadashivappa
Pages - 101 - 108     |    Revised - 15-01-2013     |    Published - 28-02-2013
Volume - 7   Issue - 1    |    Publication Date - February 2013  Table of Contents
MORE INFORMATION
KEYWORDS
Pre-processing, SMSF, Median Filter, MSE, PSNR, Correlation Coefficient, Microstructure.
ABSTRACT
The image pre-processing is very critical and important task in any digital image analysis system. The eventual success and failure of image analysis depends on the performance of preprocessing techniques applied on the image to be analyzed. In digital images, different noise types are noticed and to attenuate each type of noise, different pre-processing methods have been proposed in literature. The main focus of this paper is on pre-processing the microstructure images. Among many types of noise, impulse noise is the one which is generally noticed in microstructure images. This paper is to present a novel, efficient and suitable pre-processing method for negotiating the impulse noise that is generally present in microstructure images. Through this paper, a new filtering method, selective median switching filter (SMSF) has been proposed. The proposed method is compared with filtering methods those belong to median filter family for their efficiency in negotiating with impulse noise. The efficiency of proposed method is compared with other methods by computing the three image quality assessment methods, namely, mean square error (MSE), peak signal-to-noise ratio (PSNR) and correlation coefficient. The experimental results confirm that the proposed SMSF method is efficient in handling the impulse noise present in microstructure images of material. Also, the proposed SMSF method is quite efficient in preserving the edge information in images.
CITED BY (4)  
1 Malini, S., & Moni, R. S. (2015). Image Denoising Using Multiresolution Singular Value Decomposition Transform. Procedia Computer Science, 46, 1708-1715.
2 Hiremath, P. S., Sadashivappa, A., & Pattan, P. analysis and characterization of dendrite structures from microstructure images of material.
3 Hiremath, P. S., & Sadashivappa, A. (2014). Automated 3D Quantitative Analysis of Digital Microstructure Images of Materials using Stereology. In International Journal of Computer Applications and in proceedings of NCRAIT, National Conf. on Recent Advances in Information Technology.
4 Hiremath, P. S., Sadashivappa, A., & Pattan, P. (2014). Microstructure Image Analysis for Estimating Mechanical Properties of Ductile Cast Iron. International Journal of Computer Applications, 107(17).
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 ASM Committee. ASM Handbook: Metallography and Microstructures, Vol.9. USA:ASM International, 2004.
2 Gonzalez R.C. and Woods R.E. Digital Image Processing, 3rd Ed. USA:Pearson Publication, 2008.
3 H.Sadoghi Yazdi, F.Homayouni. “Impulsive noise suppression of images using adaptive median filter”. International Journal of Signal Processing, Image Processing and Pattern Recognition, Vol. 3, No. 3, pp. 1-12, 2010.
4 University of Cambridge. “Micrograph library”. Internet:www.doitpoms.ac.uk, Jan 5,2013.
5 M. Sonka, V.Hlavac and R. Image Processing, Analysis, and Machine Vision, 3rd Ed. USA: CL Engineering, 2007.
6 Pattan Prakash, V.D.Mytri and P.S. Hiremath. “Active Contour Multigrid Model for Segmentation and Automatic Quantification of Material Phases of Cast Iron”. International Journal of Computer Applications, Vol. 9. No.4, pp.32-37, 2010.
7 Pattan Prakash, V.D.Mytri and P.S. Hiremath. “Performance Analysis of Segmentation Methods for Automatic Quantification of Phases of Cast Iron” in proc. International conference on Computational Vision and Robotics (ICCVR), 2010, pp. 174-180.
8 J.C. Russ. The Image Processing Cook Book, 2nd Ed., Chapters 2,3,4 and 5,USA:CRC Press,2011.
9 S. E. Umbaugh. Computer Vision and Image Processing,USA:Prentice-Hall,1998.
10 S.-J. Ko and Y. H. Lee. “Center weighted median filters and their applications to image enhancement”. Circuits and Systems (IEEE Transactions), Vol. 38, No. 9, pp.984–993,1991.
11 T.C. Lin, P.T. Yu. “A new adaptive center weighted median filter for suppressing impulsive noise in images”. International Journal of Information Sciences (Elsevier), No.177, pp.1073–1087, 2007.
12 O. Yli-Harja, J. Astola, and Y. Neuvo. “Analysis of the properties of median and weighted median filters using threshold logic and stack filter representation”, Signal Processing (IEEE Transactions), Vol. 39, No. 2, pp. 395–410,1991.
13 Chen, T. and H.R. Wu. “Application of partition-based median type filters for suppressing noise in images”. Image Processing (IEEE Transactions), Vol.6, pp.829-836, 2001.
14 Ko, S.J. and Y.H. Lee. “Center weighted median filters and their applications to image enhancement. Circuits and Systems (IEEE Transactions), Vol.38, pp.984-993.1991.
15 Lin, T.C. “A new adaptive center weighted median filter for suppressing impulsive noise in images”. Journal of Information Sciences (Elsevier), Vol.177, pp. 1073-1087, 2007.
16 Lukac, R. “Performance boundaries of optimal weighted median filters”. International Journal of Image Graphics, Vol.4,pp.157-182, 2004.
17 Smolka, B. and A. Chydzinski. “Fast detection and impulsive noise removal in color images”. International Journal of Real-Time Imaging (Science Direct), Vol.11,pp.389-402, 2005.
18 Sun, T. and Y. Neuvo. 1994. “Detail-preserving median based filters in image processing”, Pattern Recognition Letters, Vol.15, pp. 341-347, 1994.
19 Wang, G., D. Li, W. Pan and Z. Zang. “Modified switching median filter for impulse noise removal. Signal Process”, Vol.90, pp.3213-3218, 2010.
20 Yin, L., R. Yang, M. Gabbouj and Y. Neuvo. “Weighted median filters: A tutorial”. Circuits and Systems. II: Analog Digital Signal Processing, Vol. 43: 157-192, 1996.
Dr. P.S. Hiremath
Gulbarga Univeristy Gulbarga - India
Mr. Anita Sadashivappa
PDA College of Engineering Gulbarga - India
anitaharsoor@gmail.com