CFP last date
22 April 2024
Reseach Article

A Study and Evaluation of Transform Domain based Image Fusion Techniques for Visual Sensor Networks

by Chaahat Gupta, Preeti Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 8
Year of Publication: 2015
Authors: Chaahat Gupta, Preeti Gupta
10.5120/20358-2555

Chaahat Gupta, Preeti Gupta . A Study and Evaluation of Transform Domain based Image Fusion Techniques for Visual Sensor Networks. International Journal of Computer Applications. 116, 8 ( April 2015), 26-30. DOI=10.5120/20358-2555

@article{ 10.5120/20358-2555,
author = { Chaahat Gupta, Preeti Gupta },
title = { A Study and Evaluation of Transform Domain based Image Fusion Techniques for Visual Sensor Networks },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 8 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 26-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number8/20358-2555/ },
doi = { 10.5120/20358-2555 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:56:33.988480+05:30
%A Chaahat Gupta
%A Preeti Gupta
%T A Study and Evaluation of Transform Domain based Image Fusion Techniques for Visual Sensor Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 8
%P 26-30
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an evaluation of different image fusion techniques. There are many image fusion techniques which have been developed in a number of applications. Image fusion incorporates the data from several images of one scene to obtain an enlightening image which is more appropriate for human visual perception or additional vision processing. Image quality is closely connected to image focus. Image fusion has become one of the most recent and popular methods in the field of image processing. The discrete cosine transforms (DCT) based methods of image fusion are more suitable for energy consumption and time-saving in real-time systems using DCT based standards of still image.

References
  1. Bai, Xiangzhi, Fugen Zhou, and Bindang Xue. "Edge preserved image fusion based on multiscale toggle contrast operator. " Image and Vision Computing29. 12 (2011): 829-839.
  2. Li, Shutao, and Bin Yang. "Multifocus image fusion by combining curvelet and wavelet transform. " Pattern Recognition Letters 29. 9 (2008): 1295-1301.
  3. Li, Qingping, et al. "Region-based multi-focus image fusion using the local spatial frequency. " Control and Decision Conference (CCDC), 2013 25th Chinese. IEEE, 2013.
  4. Wang, Jingling, et al. "Multi-spectral image fusion based on the characteristic of imaging system. "International conference on Information and Automation, 2013. IEEE, 2013.
  5. Galande, Ashwini, and Ratna Patil. "The art of medical image fusion: A survey. " Advances in Computing, Communications and Informatics (ICACCI), 2013 International Conference on. IEEE, 2013.
  6. Garg, Rishu, Preeti Gupta, and Harvinder Kaur. "Survey on multi-focus image fusion algorithms. " Engineering and Computational Sciences (RAECS), 2014 Recent Advances in. IEEE, 2014.
  7. Li, Hui, B. S. Manjunath, and Sanjit K. Mitra. "Multisensor image fusion using the wavelet transforms. " Graphical models and image processing, vol. 3, pp. 235-245. IEEE, 1997.
  8. Liu, Lixin et al. "An Effective Wavelet-based Scheme for Multi-focus Image Fusion . "Mechatronics and Automation, 2013 Takamatsu, Japan. IEEE, 2013.
  9. Haghighat, Mohammad Bagher Akbari, Ali Aghagolzadeh, and Hadi Seyedarabi. "Multi-focus image fusion for visual sensor networks in DCT domain. "Computers & Electrical Engineering 37. 5 (2011): 789-797.
  10. Om Prakash, Richa Srivastava, Ashish Khare. "Biorthogonal Wavelet Transform Based Image Fusion Using Absolute Maximum Fusion Rule. " In Image processing, 2013 International Conference on Information and Communication Technologies, pp. 577-582. IEEE, 2013.
  11. Singh, Jagdeep, and Vijay Kumar Banga. "An Enhanced DCT based Image Fusion using Adaptive Histogram Equalization. " International Journal of Computer Applications 87. 12 (2014): 26-32.
  12. O. Rockinger. "Image sequence fusions using a shift-invariant wavelet transform. " In image processing, 1997 International Conference on, vol. 3, pp. 288-291. IEEE, 1997.
  13. Y. AsnathVictyPhamila, R. Amutha. "Discrete Cosine Transform based fusion of multi-focus images for visual sensor networks. " In Signal Processing, 2013 International Conference on, pp. 161-170. IEEE, 2013.
  14. Wang, Wencheng, and Faliang Chang. "A multi-focus image fusion method based on Laplacian pyramid. " Journal of Computers 6. 12 (2011): 2559-2566.
  15. Ali, Syed Twareque, Jean-Pierre Antoine, and Jean-Pierre Gazeau. "Discrete Wavelet Transforms. " Coherent States, Wavelets, and Their Generalizations. Springer New York, 2014. 379-410.
  16. Haghighat, Mohammad Bagher Akbari, Ali Aghagolzadeh, and Hadi Seyedarabi. "Real-time fusion of multi-focus images for visual sensor networks. " Machine Vision and Image Processing (MVIP), 2010 6th Iranian. IEEE, 2010.
  17. Patil, U. ; Mudengudi, U. , "Image fusion using hierarchical PCA. ," Image Information Processing (ICIIP), 2011 International Conference on , pp. 1-6, 2011.
  18. Wen Cao, Bicheng Li, Yong Zhang, "A remote sensing image fusion method based on PCA transform and wavelet packet transform," Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on , Vol. 2, pp. 976-981, 2003.
  19. Mahajan Rajiv, Bamba Sheffali, "Performance Evaluation of Modified Color Based Edge Detection of Remote Sensing Images Using Fuzzy Logic," International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 8, August 2014,pp. 334-343.
Index Terms

Computer Science
Information Sciences

Keywords

Image Fusion Discrete Wavelet Transform Discrete Cosine Transformations Wavelet Transformations Laplacian Pyramid Visual Sensor Networks.