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Real-Time Implementation of Multi-Imaging Sensor Data Fusion Techniques

Published on July 2018 by B. Hela Saraswathi, Praveen C, Vps Naidu
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National Conference on Electronics, Signals and Communication
Foundation of Computer Science USA
NCESC2017 - Number 1
July 2018
Authors: B. Hela Saraswathi, Praveen C, Vps Naidu
7afc8010-bbb4-4fb9-8fff-3cd978796fd4

B. Hela Saraswathi, Praveen C, Vps Naidu . Real-Time Implementation of Multi-Imaging Sensor Data Fusion Techniques. National Conference on Electronics, Signals and Communication. NCESC2017, 1 (July 2018), 27-37.

@article{
author = { B. Hela Saraswathi, Praveen C, Vps Naidu },
title = { Real-Time Implementation of Multi-Imaging Sensor Data Fusion Techniques },
journal = { National Conference on Electronics, Signals and Communication },
issue_date = { July 2018 },
volume = { NCESC2017 },
number = { 1 },
month = { July },
year = { 2018 },
issn = 0975-8887,
pages = { 27-37 },
numpages = 11,
url = { /proceedings/ncesc2017/number1/29608-7041/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Electronics, Signals and Communication
%A B. Hela Saraswathi
%A Praveen C
%A Vps Naidu
%T Real-Time Implementation of Multi-Imaging Sensor Data Fusion Techniques
%J National Conference on Electronics, Signals and Communication
%@ 0975-8887
%V NCESC2017
%N 1
%P 27-37
%D 2018
%I International Journal of Computer Applications
Abstract

Enhanced Vision System (EVS) is one of the most advanced technologies that provide good situational awareness to the pilot, which is essential to fly safely under poor visibility conditions. EVS uses Electro-Optical (EO) and Infra-Red (IR) imaging sensors. Individual images obtained from these sensors provide different information of the terrain and surroundings, but when they are fused, it gives better information which improves the visual perception. Fusion of images obtained from such multi-sensors can be achieved using different techniques. For fusing the EO and IR images of EVS, four fusion methods viz. , Alpha Blending, Principal Component Analysis (PCA), Laplacian Pyramid, and Discrete Wavelet Transform (DWT) have been implemented and tested. Laplacian pyramid based image fusion technique proved to provide better fusion when compared to the other techniques.

References
  1. R. Johnson Suthakar, J. Monica Esther M. E, D. Annapoorani, F. Richard Singh Samuel,"Study of Image Fusion - Techniques, Method and Applications", IJCSMC, Vol. 3, Issue. 11, November 2014
  2. Gonzalez, R. C. & Wintz, P. Digital image processing. Addison-Wesley, MA, 1987
  3. Sukhpreet Singh, Rachna Rajput, "Multiple Image Fusion Using Laplacian Pyramid", International Journal Of Engineering And Computer Science, Vol. 3, Issue 12, December 2014
  4. V. P. S. Naidu, J. R Raol, "Pixel-level Image Fusion using Wavelet and Principal Component Analysis", Defence Science Journal, Vol. 58, No. 3, May 2008.
  5. V. P. S. Naidu, L. Garlin Delphina, "Assessment of Color and Infrared images using No-reference Image Quality Metrics", Proceedings of NCATC 2011
Index Terms

Computer Science
Information Sciences

Keywords

Electro-optical Infra-red Multi-sensors