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Comparative Analysis of Image Enhancement Technique for Hyperspectral Palmprint Images

by Anita G. Khandizod, R.r. Deshmukh
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 23
Year of Publication: 2015
Authors: Anita G. Khandizod, R.r. Deshmukh
10.5120/21842-5115

Anita G. Khandizod, R.r. Deshmukh . Comparative Analysis of Image Enhancement Technique for Hyperspectral Palmprint Images. International Journal of Computer Applications. 121, 23 ( July 2015), 30-35. DOI=10.5120/21842-5115

@article{ 10.5120/21842-5115,
author = { Anita G. Khandizod, R.r. Deshmukh },
title = { Comparative Analysis of Image Enhancement Technique for Hyperspectral Palmprint Images },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 23 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number23/21842-5115/ },
doi = { 10.5120/21842-5115 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:09:14.082126+05:30
%A Anita G. Khandizod
%A R.r. Deshmukh
%T Comparative Analysis of Image Enhancement Technique for Hyperspectral Palmprint Images
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 23
%P 30-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image Enhancement is one of the most important and difficult techniques, also the first stage in the pre-processing of images which have to be subjected to image recognition algorithms. The goal of image enhancement is to improve the quality of images. Palmprint image quality is an important factor in the performance of hyperspectral palmprint recognition system. To the best of knowledge there is no evidence of work specifically directed towards image enhancement techniques on hyperspectral palm print images. In this paper different thirteen types of image enhancement techniques are compared based on image quality measure (subjective and objective), subjective image quality measure based on histogram and objective quality measure is based on mean square error (MSE), Peak signal to noise ratio (PSNR), Normalized cross correlation (NK), Average difference (AD), Structural content (SC), Maximum difference (MD), Normalized absolute error (NAE). Such a comparison would be useful in determining the best suited image enhancement method for hyperspectral palmprint. Median filter gives good performance as compare to other image enhancement techniques. The performance of different thirteen image enhancement techniques are tested on PolyU hyperspectral palmprint database. The comparative results are tabled.

References
  1. Youhei Terai, Tomio Goto, "Color Image Enhancement," Proceedings of IEEE, pp-392-393, Iligan City, 2009.
  2. Anita G. Khandizod, R. R. Deshmukh, "Analysis and Feature Extraction using Wavelet based Image Fusions for Multispectral Palmprint Recognition", International Journal of Enhanced Research in Management & Computer Applications, ISSN: 2319-7471 Vol. 3 Issue 3, March-2014, pp: (57-64), Impact Factor: 1. 147, Available online at: www. erpublications. com.
  3. Anita G. Khandizod, R. R. Deshnukh, Ramesh. R. Manza, "Wavelet-based image fusion and quality assessment of Multispectral Palmprint Recognition", 2nd National Conference on Computer Communication and Information Technology, sinhgad Institute of Computer Science, Pandharpur, NC2IT-2013.
  4. Sonja Grgi, Mislav Grgi, Marta Mrak, "RELIABILITY OF OBJECTIVE PICTURE QUALITY MEASURES," Journal of ELECTRICAL ENGINEERING, VOL. 55, NO. 1-2, 3-10, ISSN 1335- 3632. 2004.
  5. Department of Computing, the Hong Kong Polytechnic University (PolyU), Hyperspectral Palmprint database, PolyU, accessed on Aug. 22, 2013, available at: : http://www4. comp. polyu. edu. hk/~biometrics/Hyperspectral Palmprint /HSP . htm. K. Elissa, "Title of paper if known," unpublished.
  6. YAN-xin SHI, CHENG Yong-mei1, "Adaptive Filter for Color Impulsive Removal Based on the HSI Color Space," 2011M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science, 1989.
  7. Huang, T. S. , G. J. Yang, and G. Y. Tang. "A fast two-dimensional median filtering algorithm. ", IEEE transactions on Acoustics, Speech and Signal Processing, Vol ASSP 27, No. 1, February 1979
  8. Zhenhua Guo, David Zhang, Lei Zhang, and Wenhuang Liu, "Feature Band Selection for Online Multispectral Palmprint Recognition", IEEE transactions on information forensics and security, vol. 7, no. 3, June 2012.
  9. Anita G. Khandizod, R. R. Deshmukh, "Multispectral Palm print Image Fusion- A Review", International Journal of Engineering Research & Technology (IJERT), ISSN: 2278-01s81, Vol. 3 Issue 2, February – 2014.
  10. Saruchi , "Adaptive Sigmoid Function to Enhance Low Contrast Images International Journal of Computer Applications (0975 –8887) Volume 55 – No. 4, October 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Image Enhancement image quality measure Spatial and frequency Domain Image restoration

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