Sensor noise effects on signal-level image fusion performance.

Petrovic, Vladimir S. and Xydeas, Costas (2003) Sensor noise effects on signal-level image fusion performance. Information Fusion, 4 (3). pp. 167-183. ISSN 1566-2535

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The aim of this paper is twofold: (i) to define appropriate metrics which measure the effects of input sensor noise on the performance of signal-level image fusion systems and (ii) to employ these metrics in a comparative study of the robustness of typical image fusion schemes whose inputs are corrupted with noise. Thus system performance metrics for measuring both absolute and relative degradation in fused image quality are proposed when fusing noisy input modalities. A third metric, which considers fusion of noise patterns, is also developed and used to evaluate the perceptual effect of noise corrupting homogenous image regions (i.e. areas with no salient features). These metrics are employed to compare the performance of different image fusion methodologies and feature selection/information fusion strategies operating under noisy input conditions. Altogether, the performance of seventeen fusion schemes is examined and their robustness to noise considered at various input signal-to-noise ratio values for three types of sensor noise characteristics.

Item Type: Journal Article
Journal or Publication Title: Information Fusion
Additional Information: The novel and leading, both chronologically and technically, concepts of this paper on objective image fusion metrics as applied to practical noisy input modalities provided for the first time researchers with the means i) to carry out subjectively meaningful comparative assessments of different image fusion algorithms and ii) to accurately and efficiently optimise fusion algorithms. This work has been identified and supported by BAES, Warton ( Dr. D. Parker) for aerospace applications. RAE_import_type : Journal article RAE_uoa_type : Electrical and Electronic Engineering
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/qa75
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 2607
Deposited By: ep_importer
Deposited On: 28 Mar 2008 10:32
Refereed?: Yes
Published?: Published
Last Modified: 06 Aug 2019 00:46

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