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Improving fusion of surveillance images in sensor networks using independent component analysis

Research output: Contribution to journalArticle

Original languageEnglish
Pages1029 - 1035
Number of pages7
JournalIEEE Transactions on Consumer Electronics
Journal publication dateAug 2007
Journal issue3
Volume53
DOIs
StatePublished

Abstract

In this paper we present a novel algorithm for fusion of multimodal surveillance images, based on ICA, which has an improved performance over sensor networks. Improvements have been demonstrated through separate training process for different modalities and the use of a fusion metric to maximise the quality of the fused image. Sparse coding of the coefficients in ICA domain is used to minimize noise transferred from input images into the fused output. Experimental results confirm that the proposed method outperforms other state-of-the-art methods in the sensor network environment, characterized by JPEG 2000 compression and data packetization.

Additional information

Publisher: Institute of Electrical and Electronics Engineers Rose publication type: Journal article Sponsorship: This work has been funded by the UK Data and Information Fusion Defence Technology Centre (DIF DTC). Terms of use: Copyright © 2007 IEEE. Reprinted from IEEE Transactions on Consumer Electronics. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Research areas

  • image fusion, fusion metrics, sensor networks, JPEG 2000, component analysis

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