CFP last date
20 January 2025
Reseach Article

An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization

by Jagdeep 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: Jagdeep Singh, Vijay Kumar Banga
10.5120/15262-3955

Jagdeep Singh, Vijay Kumar Banga . An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization. International Journal of Computer Applications. 87, 12 ( February 2014), 26-32. DOI=10.5120/15262-3955

@article{ 10.5120/15262-3955,
author = { Jagdeep Singh, Vijay Kumar Banga },
title = { An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 12 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number12/15262-3955/ },
doi = { 10.5120/15262-3955 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:45.368953+05:30
%A Jagdeep Singh
%A Vijay Kumar Banga
%T An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 12
%P 26-32
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Image fusion fuses the information from several images of one scene to obtain a precise, complete and reliable image which is more appropriate for human visual perception or additional vision processing. The quality of an image is closely related to image focus. The discrete cosine transforms (DCT) based methods of image fusion are more suitable and time-saving in real-time systems using DCT based standards of still image or video. DCT based image fusion produced results but with lesser clarity, less PSNR value and more Mean square error. This paper proposes a new algorithm whose overall objective is to improve the results by combining DCT with adaptive histogram equalization. The experimental results and comparison has shown that the proposed algorithm provides a significant improvement over the existing DCT based fusion techniques.

References
  1. Pei, Yijian, Huayu Zhou, Jiang Yu, and Guanghui Cai, "The improved wavelet transform based image fusion algorithm and the quality assessment", IEEE 3rd International Conference on Image and Signal Processing (CISP), vol. 1, pp. 219-223, 16-18 Oct. 2010.
  2. Haifeng Liu, Mike Deng, Chuangbai Xiao, and Xiao Xu, "Image fusion algorithm based on adaptive weighted coefficients", IEEE 10th International Conference on Signal Processing (ICSP), Beijing, pp. 748-751, 24-28 Oct. , 2010.
  3. Haghighat, Mohammad Bagher Akbari, Ali Aghagolzadeh, and Hadi Seyedarabi, "Real-time fusion of multi-focus images for visual sensor networks", IEEE 6th Iranian Machine Vision and Image Processing (MVIP),Isfahan, pp. 1-6, 27-28 Oct. , 2010.
  4. Cao, Jian-zhong, Zuo-feng Zhou, Hao Wang, and Wei-hua Liu. "Multifocus Noisy Image Fusion Algorithm Using the Contourlet Transform. ", IEEE International Conference on Multimedia Technology (ICMT) Ningbo, pp. 1-4, 29-31 Oct. , 2010.
  5. Mohamed, M. A. , and B. M. El-Den. "Implementation of image fusion techniques for multi-focus images using FPGA", IEEE 28th National Radio Science Conference (NRSC), Cairo, pp. 1-11, 26-28 April, 2011.
  6. Lavanya, A. , K. Vani, S. Sanjeevi, and R. S. Kumar, "Image fusion of the multi-sensor lunar image data using wavelet combined transformation" IEEE International Conference on Recent Trends in Information Technology (ICRTIT), pp. 920-925, 3-5 June, 2011.
  7. Ren, Haozheng, Yihua Lan, and Yong Zhang. "Research of multi-focus image fusion based on M-band multi-wavelet transformation", IEEE Fourth International Workshop on Advanced Computational Intelligence (IWACI), Wuhan, pp. 395-398, 19-21 Oct. , 2011.
  8. Patil, Ujwala, and Uma Mudengudi. "Image fusion using hierarchical PCA" IEEE International Conference on Image Information Processing (ICIIP), pp. 1-6, 3-5 Nov. , 2011.
  9. Chu-Hui Lee and Zheng-Wei Zhou, "Comparison of Image Fusion based on DCT-STD and DWT-STD", International Multi-Conference of Engineers and Computer scientists 2012 Vol. I, IMECS2012, Hong Kong, March 14-16, 2012.
  10. Prakash, Chandra, S. Rajkumar, and P. V. S. S. R. Mouli. "Medical image fusion based on redundancy DWT and Mamdani type min-sum mean-of-max techniques with quantitative analysis" IEEE International Conference on Recent Advances in Computing and Software Systems (RACSS), pp. 54-59, 25-27 April, 2012.
  11. Parmar, Kiran, Rahul K. Kher, and Falgun N. Thakkar. "Analysis of CT and MRI Image Fusion Using Wavelet Transform. " IEEE International Conference on Communication Systems and Network Technologies (CSNT), pp. 124-127, 11-13 May, 2012.
  12. S. Zebhi, M. R. Aghabozorgi Sahaf, M. T. Sadeghi, "Image fusion using PCA in CS domain", An International Journal of Signal & Image Processing, Vol. 3, No. 4, August 2012.
  13. Desale, Rajenda Pandit, and Sarita V. Verma. "Study and analysis of PCA, DCT & DWT based image fusion techniques" IEEE International Conference on Signal Processing Image Processing & Pattern Recognition (ICSIPR), Coimbatore, pp. 66-69, 7-8 Feb. , 2013.
  14. Bedi S. S, Agarwal Jyoti, Agarwal Pankaj, "Image fusion techniques and quality assessment parameters for clinical diagnosis: A Review", International journal of advanced research in computer and communication engineering Vol. (2), issue 2, pp. 1153-1157, February 2013.
  15. Sruthy, S. , Latha Parameswaran, and Ajeesh P. Sasi. "Image Fusion Technique using DT-CWT", IEEE International Multi-Conference on automation, computing, control, communication & compressed sensing (iMac4S), Kottayam, pp. 160-164, 22-23 March, 2013.
  16. http://eoedu. belspo. be/en/guide/fusion. asp?section=3. 11. 2
  17. www. mathworks. inhelpimages efdct2. html.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete Cosine Transformation (DCT) Image Fusion Principle Component Analysis Adaptive histogram equalization