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Multi-Imaging Sensor Data Fusion using 2D DST

Published on July 2018 by M. Divya, S. Aruna Mastani, Vps Naidu
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National Conference on Electronics, Signals and Communication
Foundation of Computer Science USA
NCESC2017 - Number 3
July 2018
Authors: M. Divya, S. Aruna Mastani, Vps Naidu
eb7a605a-a40f-40d3-82a9-339b249ea430

M. Divya, S. Aruna Mastani, Vps Naidu . Multi-Imaging Sensor Data Fusion using 2D DST. National Conference on Electronics, Signals and Communication. NCESC2017, 3 (July 2018), 4-9.

@article{
author = { M. Divya, S. Aruna Mastani, Vps Naidu },
title = { Multi-Imaging Sensor Data Fusion using 2D DST },
journal = { National Conference on Electronics, Signals and Communication },
issue_date = { July 2018 },
volume = { NCESC2017 },
number = { 3 },
month = { July },
year = { 2018 },
issn = 0975-8887,
pages = { 4-9 },
numpages = 6,
url = { /proceedings/ncesc2017/number3/29619-7091/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Electronics, Signals and Communication
%A M. Divya
%A S. Aruna Mastani
%A Vps Naidu
%T Multi-Imaging Sensor Data Fusion using 2D DST
%J National Conference on Electronics, Signals and Communication
%@ 0975-8887
%V NCESC2017
%N 3
%P 4-9
%D 2018
%I International Journal of Computer Applications
Abstract

Image fusion is a process of combining two or more images into a single image without any loss of information. Now-a-days, image fusion is playing a major role in current research areas. In this paper, a new data fusion algorithm is presenting called discrete sine transform based multi imaging sensor data fusion algorithm. Here multi imaging sensor data fusion using 2D-DST is developed, implemented and tested using image fusion quality evaluation metrics. The proposed fusion algorithms were compared with discrete Cosine transform based fusion algorithms and it is observed from the results that they are almost similar and comparable. The proposed fusion algorithms are computationally simple and could be used in real time applications.

References
  1. https://en. wikipedia. org/wiki/Image_fusion(September-2017)
  2. Vladimir Britanak, Patrick C. Yiop and K. R. Rao, Discrete cosine and Sine Transforms, Academic Press, 2007.
  3. R. C. Gonzalez and P. Wintz, Digital Image Processing, MA: Addison-Wesley, 1987. ( (September-2017)
  4. https://en. wikipedia. org/wiki/Discrete_sine_transform (September-2017)
  5. VPS Naidu, "Discrete Cosine Transform based Image Fusion Techniques", Journal of Communication, Navigation and Signal Processing (January 2012) Vol. 1, No. 1, pp. 35-45. Bowman, M. , Debray, S. K. , and Peterson, L. L. 1993. Reasoning about naming systems.
  6. VPS Naidu, Multi-Resolution Image Fusion by FFT, ICIIP-2011, 3-5 Nov. 2011. (IEEE DoI: 10. 1109/ICIIP. 2011. 6108862).
  7. VPS Naidu, M. Divya, P. Maha Lakshmi, "Multi-Modal Medical Image Fusion using Multi-Resolution Discrete Sine Transform", Control and Data Fusion eJournal: CADFEJL Vol. 1, No. 2, pp. 13-27, Mar-Apr 2017.
  8. V. P. S. Naidu and J. R. Raol, "Pixel-level Image Fusion using Wavelets and Principal Component Analysis", Defence Science Journal, Vol. 58, No. 3, May 2008, pp. 338-352.
Index Terms

Computer Science
Information Sciences

Keywords

Discrete Sine Transform Image Fusion Discrete Cosine Transform.