CFP last date
20 May 2024
Reseach Article

Image Enhancement Techniques using Highpass and Lowpass Filters

by Aziz Makandar, Bhagirathi Halalli
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 109 - Number 14
Year of Publication: 2015
Authors: Aziz Makandar, Bhagirathi Halalli
10.5120/19256-0999

Aziz Makandar, Bhagirathi Halalli . Image Enhancement Techniques using Highpass and Lowpass Filters. International Journal of Computer Applications. 109, 14 ( January 2015), 21-27. DOI=10.5120/19256-0999

@article{ 10.5120/19256-0999,
author = { Aziz Makandar, Bhagirathi Halalli },
title = { Image Enhancement Techniques using Highpass and Lowpass Filters },
journal = { International Journal of Computer Applications },
issue_date = { January 2015 },
volume = { 109 },
number = { 14 },
month = { January },
year = { 2015 },
issn = { 0975-8887 },
pages = { 21-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume109/number14/19256-0999/ },
doi = { 10.5120/19256-0999 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:44:47.038809+05:30
%A Aziz Makandar
%A Bhagirathi Halalli
%T Image Enhancement Techniques using Highpass and Lowpass Filters
%J International Journal of Computer Applications
%@ 0975-8887
%V 109
%N 14
%P 21-27
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Digital image processing refers to the process of digital images by means of digital computer. The main application area in digital image processing is to enhance the pictorial data for human interpretation. In image acquisition some of the unwanted information is present that will be removed by several preprocessing techniques. Filtering helps to enhance the image by removing noise. The aim of this paper is to demonstrate the lowpass and highpass filtering techniques, however they are the filtering techniques used in Fourier and Wavelet Transformations. In Wavelet Transform these two filters play an important role in reconstructing the original image by using subband coding. Lowpass filter will produce a Gaussian smoothing blur image, in the other hand, high pass filter will increase the contrast between bright and dark pixel to produce a sharpen image.

References
  1. R. Gonzalez & R. Wood, "Digital Image Processing," 3rd ed, Englewood Cliffs, NJ: Prentice Hall, 2007.
  2. BH Brinkmann, A Manduca, RA Robb, "Optimized homomorphic unsharp masking for MR grayscale inhomogeneity correction," Medical Imaging, IEEE Transactions on journal on Medical imaging, Vol. 17. 2011.
  3. J. S. Lee, "Digital image enhancement and noise filtering by use of local statistics," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 2, no. 3, pp. 165-168.
  4. Randall B. Smith, "Filtering Images," Ph. D thesis 5 January 2012 ©MicroImages, http://www. microimages. com/documentation/Tutorials/filter. pdf
  5. J. S. Lee, "Digital image smoothing and the sigma filter," Computer Vision, Graphics and Image Processing, vol. 24, pp. 255-269, 1983.
  6. Roopashree. S, Sachin Saini, Rohan Ranjan Singh, "Enhancement and Pre-Processing of Images Using Filtering," International Journal of Engineering and Advanced Technology (IJEAT), Volume-1, Issue-5, June 2012
  7. A. Polesel, G. Ramponi and V. J. Mathews, "Image Enhancement via Adaptive Unsharp Masking," IEEE Trans. Image Processing , Vol. 9, No. 3, pp. 505-510, March 2000.
  8. Buades A. , Coll B. and Morel J. M Ozaki, Y. Adachi, Y. Iwahori, and N. Ishii, Application of fuzzy theory to writer recognition of Chinese characters, International Journal of Modelling and Simulation, 18(2), pp 112-116, 1998.
  9. Aziz Makandar, Daneshwari Mulimani, Mahantesh Jevoor, "Comparative Study of Different Noise Models and Effective Filtering Techniques," International Journal of Science and Research (IJSR),Volume 3 Issue 8,pp 458- 464, August 2014
  10. J. K. Romberg, M. B. Wakin, and R. G. Baraniuk, "Multiscale geometric image processing," in Proceedings of the SPIE: Visual Communications and Image Processing 2003, pp. 1265-1272, 2003.
  11. R. R. Coifman and D. L. Donoho, "Translation invariant de-noising: Wavelets and statistics," NewYork: Springer-Verlag, 1995.
  12. A. L. Da Cunha, J. Zhou, and M. N. Do, "The Nonsubsampled Contourlet Transform: Theory, Design,and Applications," IEEE Trans. Image Process, vol. 15, pp. 3089-3101, 2006.
  13. D. Donoho, I. Johnstone, G. Kerkyacharian, D. Picard, "Wavelet shrinkage: asymptopia?," Journal of the Royal Statistical Society B, vol. 57, pp. 301-369, 1995
  14. Philippe Cattin, "Image Restoration: Introduction to Signal and Image Processing," MIAC, University of Basel.
  15. O. Ozsen, "Early Detection of Breast Cancer Using Mathematical Morphology," in Knowledge-Based Intelligent Information and Engineering Systems, pp. 583-590, 2004.
  16. Omeed Kamal Khorsheed, "Produce low-pass and high-pass image filter in java," International Journal of Advances in Engineering & Technology, pp. 712-722, July 2014.
  17. Image Processing - Laboratory 9, "Image filtering in the spatial and frequency domains," Technical University of Cluj-Napoca
  18. Nagao M and Matsuyama T. (1997), "Computer Graphics and ImageProcessing," vol. 9, pp. 394-407.
  19. Robert Fisher, Simon Perkins, Ashley Walker, Erik Wolfart, 2004, "The Hypermedia Image Processing Reference," http://homepages. inf. ed. ac. uk/rbf/HIPR2/unsharp. htm
  20. B. S. Anami, D. G. Savakar, Aziz Makandar, and P. H. Unki (2005), "A Neural Network Model for Classification of Bulk Grain Samples Based on HSI and Texture," in proceedings of International Conference on Cognition and Recognition, pages 359-368.
  21. Aghagolzadeh S. and Ersory O. K, "Transform image Enhancement," Optical Engineering, vol. 31, pp. 614-626,1992.
  22. Herman J. Blinchikoff, Anatol I. Zverev, "Filtering in the Time and Frequency Domains".
Index Terms

Computer Science
Information Sciences

Keywords

Fast Fourier Transform (FFT) Lowpass Filter Highpass Filter Wavelet Transform.