DOI | Resolve DOI: https://doi.org/10.1109/NAECON.2011.6183109 |
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Author | Search for: Blasch, E.P.; Search for: Liu, Z.1 |
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Affiliation | - National Research Council of Canada
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Format | Text, Article |
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Conference | 2011 IEEE National Aerospace and Electronics Conference, NAECON 2011, 20 July 2011 through 22 July 2011, Fairborn, OH |
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Subject | Biomedical images; Electro-optical; Entropy-based; Evaluation; Fused images; Image fusion methods; Image fusion metrics; Infrared imagery; Land cover; LANDSAT; Landsat imagery; LANDSAT satellite images; Metrics; Multi-spectral; Night vision; Structural similarity; Diagnosis; Image fusion; Vision; Satellite imagery |
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Abstract | Image fusion is an important component of many applications such as inspection, night vision, medical diagnosis, and electro-optical (multispectral) targeting. In this paper, we build upon our previous results for image fusion metrics by applying the methods to satellite imagery versus night vision (visual and infrared imagery) and single-metric biomedical image fusion analysis. Multispectral examples include satellite imagery for land-cover analysis. In this paper, we explore a variety of metrics that have been used to quantify the performance of the fused image products. The exhaustive conclusive analysis over all possibilities is not realizable, so in this paper we group the various metrics into categories and demonstrate an application of the metrics to satellite LANDSAT imagery using an entropy-based image fusion method. From the many metrics analyzed, we found the Image Structural Similarity Based (ISSB) metrics are most useful. © 2011 IEEE. |
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Publication date | 2011 |
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In | |
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Language | English |
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Peer reviewed | Yes |
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NPARC number | 21271645 |
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Export citation | Export as RIS |
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Report a correction | Report a correction (opens in a new tab) |
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Record identifier | 32697f21-6785-4305-bb45-17ec04ae8687 |
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Record created | 2014-03-24 |
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Record modified | 2020-04-21 |
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