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Reseach Article

Dynamic Non-Linear Enhancement using Gamma Correction and Dynamic Restoration

by Parambir Singh, Vijay Kumar Banga
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 12
Year of Publication: 2014
Authors: Parambir Singh, Vijay Kumar Banga
10.5120/15263-3956

Parambir Singh, Vijay Kumar Banga . Dynamic Non-Linear Enhancement using Gamma Correction and Dynamic Restoration. International Journal of Computer Applications. 87, 12 ( February 2014), 33-40. DOI=10.5120/15263-3956

@article{ 10.5120/15263-3956,
author = { Parambir Singh, Vijay Kumar Banga },
title = { Dynamic Non-Linear Enhancement using Gamma Correction and Dynamic Restoration },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 12 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 33-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number12/15263-3956/ },
doi = { 10.5120/15263-3956 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:46.033883+05:30
%A Parambir Singh
%A Vijay Kumar Banga
%T Dynamic Non-Linear Enhancement using Gamma Correction and Dynamic Restoration
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 12
%P 33-40
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper has proposed a new integrated image enhancement algorithm by integrating non linear image enhancement technique with dynamic restoration. Image processing plays a vital role in visualization application. It improves the visibility of poor images. Different techniques have been proposed so far. To improve image quality image enhancement can selectively enhance and restrain some information about image. It is a method which decreases image noise, eliminate artifacts, and maintain details. Its purpose is to amplify certain image features for analysis, diagnosis and display. The overall objective of this paper is to propose an integrated technique which will integrate the nonlinear enhancement technique with the gamma correction and dynamic restoration technique. The proposed algorithm is implemented in MATLAB. Experimental results have shown quite significant results over the available methods.

References
  1. Crespo, J. , Maojo, V. ; Herrero, C. ; Sanandres, J. A, "Enhancement of MR images using non-linear techniques" 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Amsterdam, pp. 752-753, Nov. 1996.
  2. Y. T. Kim, "Contrast enhancement using brightness preserving bi- histogram equalization", IEEE Transactions on Consumer Electronics Suwon, Korea Vol. 43, pp. 1- 8, Feb. 1997.
  3. Arigela, Saibabu, and K. Vijayan Asari. "An Adaptive and Non Linear Technique for Enhancement of Extremely High Contrast Images. " 35th IEEE Applied Imagery and Pattern Recognition Workshop, Norfolk, Virginia, USA. pp. 24-24, April 2006.
  4. Lung-Jen Wang, Ya-Chun Huang "An Improved Non-Linear Image Enhancement Method for Video Coding" International Conference on Complex, Intelligent and Software Intensive Systems in Barcelona Spain, pp. 79- 84, March 2008.
  5. Unaldi, N. , Temel, S. ; Asari, V. K. ; Rahman, Z. -u. "An automatic wavelet-based nonlinear image enhancement technique for aerial imagery" 4th International Conference on Recent Advance in Space Technology, Istanbul ,Turkey, pp. 307-312, June 2009.
  6. Hossain, Md Foisal, Mohammad Reza Alsharif, and Katsumi Yamashita. "Medical image enhancement based on nonlinear technique and logarithmic transform coefficient histogram matching. ", 2010 IEEE/ICME International Conference on Complex Medical Engineering (CME), Gold Coast, Australia pp. 58-62. July, 2010.
  7. Lung-Jen Wang, Ya-Chun Huang, "Non-Linear Image Enhancement Using Opportunity Costs" Second International Conference on Computational Intelligence, Communication Systems and Networks, Liverpool, pp. 256-261, July 2010.
  8. Xizhen Han , Zhao Jian "A nonlinear image enhancement algorithm based on partial differential equations", IEEE 10th International Conference on Signal Processing (ICSP), in Beijing China Oct. 2010.
  9. Deepak Ghimire, Joonwhoan Lee, "Nonlinear Transfer Function-Based Local Approach for Color Image Enhancement", IEEE Transactions on Consumer Electronics, Vol. 57, issue. 2, , pp. 858-865 May 2011.
  10. Ullah, I. , and S. H. Amin. "Application of image enhancement techniques for shape reconstruction using shape from shading. " IEEE International Conference on Computer Networks and Information Technology (ICCNIT), Peshawar Campus, Pakistan, pp. 315-318, July 2011.
  11. Lizhu Liu, Haiying Wang, "Image Enhancement Using a Nonlinear Method with an Improved Single-Scale Retinex Algorithm" International Conference on Electronics, Communications and Control (ICECC), Ningbo China, pp. 2086-2089, Sept. 2011. Sept. 2011.
  12. Murahira, Kota, and Akira Taguchi. "Hue-Preserving Color Image Enhancement in RGB Color Space with Rich Saturation. "IEEE International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) in New Taipei Taiwan. pp 266-269, Nov. 2012.
  13. Vishwakarma, Anish Kumar, Agya Mishra, Kumar Gaurav, and Abhishek Katariya. "Illumination Reduction for Low Contrast Color Image Enhancement with Homomorphic Filtering Technique. " IEEE International Conference on Communication Systems and Network Technologies (CSNT), Rajkot, Gujarat, India, pp. 171-173, May 2012.
  14. Wang, Lung-Jen, and Ya-Chun Huang. "Combined Opportunity Cost and Image Classification for Non-Linear Image Enhancement. " IEEE Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), Palermo, Italy, pp. 135-140. July 2012.
  15. Sunanda. S Alur and M. C Hanumantharaju, "A Novel Approach Based On wavelet and Non-Linear Transfer Function-Based Local Approach for Real Color Image Enhancement", IEEE International Conference on Computing Sciences, Punjab, India pp. 1-6, September 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Image enhancement human visual perception Visibility Dynamic restoration gamma correction