Video Fusion Using Pixel Averaging, Principal Component Analysis and Laplacian Pyramid - A Comparative Study

In this paper, performances of various video fusion algorithms are compared by applying them to a set of infrared (IR) and visible band videos. The application of interest is area surveillance and the fusion process aims at integration of complementary information from multi-sensor inputs for enhanc...

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Bibliographic Details
Published inInternational journal of advanced computer research Vol. 2; no. 4; p. 169
Main Authors Prasad, P Surya, Poornesh, P, Sekhar, P N R L Chandra
Format Journal Article
LanguageEnglish
Published Bhopal Accent Social and Welfare Society 01.12.2012
Subjects
Algorithms
Human
Infrared
Perception
Pixels
Principal component analysis
Pyramids
Surveillance
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Summary:In this paper, performances of various video fusion algorithms are compared by applying them to a set of infrared (IR) and visible band videos. The application of interest is area surveillance and the fusion process aims at integration of complementary information from multi-sensor inputs for enhancing the human perception of the monitored scene and to make the result suitable for further processing. The performance of algorithms viz. pixel averaging, principal component analysis and Laplacian pyramid are compared. A set of measures of effectiveness for comparative performance analysis like Fusion Factor and Fusion Symmetry are defined and applied on the output of the above fusion algorithms.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
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ISSN:2249-7277
2277-7970