Petrovic, V. and Xydeas, C. (2005) Objective image fusion performance characterisation. In: Computer Vision, 2005. ICCV 2005. Tenth IEEE International Conference on :. IEEE, pp. 1866-1871. ISBN 0-7695-2334-XFull text not available from this repository.
mage fusion as a way of combining multiple image signals into a single fused image has in recent years been extensively researched for a variety of multisensor applications. Choosing an optimal fusion approach for each application from the plethora of algorithms available however, remains a largely open issue. A small number of metrics proposed so far provide only a rough, numerical estimate of fusion performance with limited understanding of the relative merits of different fusion schemes. This paper proposes a method for comprehensive, objective, image fusion performance characterisation using a fusion evaluation framework based on gradient information representation. The method provides an in-depth analysis of fusion performance by quantifying: information contributions by each sensor, fusion gain, fusion information loss and fusion artifacts (artificial information created). It is demonstrated on the evaluation of an extensive dataset of multisensor images fused with a wide range of established image fusion algorithms. The results demonstrate and quantify a number of well known issues concerning the performance of these schemes and provide a useful insight into a number of more subtle yet important fusion performance effects not immediately accessible to an observer.
|Item Type:||Contribution in Book/Report/Proceedings|
|Subjects:||?? qa75 ??|
|Departments:||Faculty of Science and Technology > School of Computing & Communications|
|Deposited On:||12 Oct 2012 13:35|
|Last Modified:||23 Mar 2017 20:36|
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