Objective assessment of multiresolution image fusion algorithms for context enhancement in night vision: a comparative study

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DOIResolve DOI: http://doi.org/10.1109/TPAMI.2011.109
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TypeArticle
Journal titleIEEE Transactions on Pattern Analysis and Machine Intelligence
ISSN0162-8828
Volume34
Issue1
Article number5770270
Pages94109; # of pages: 16
SubjectMulti-resolutions; Night vision; objective fusion assessment; Performance metrices; Pixel-level image fusion; Algorithms; Feature extraction; Image quality; Image resolution; Processing; Quality control; Rating; Vision; Image fusion
AbstractComparison of image processing techniques is critically important in deciding which algorithm, method, or metric to use for enhanced image assessment. Image fusion is a popular choice for various image enhancement applications such as overlay of two image products, refinement of image resolutions for alignment, and image combination for feature extraction and target recognition. Since image fusion is used in many geospatial and night vision applications, it is important to understand these techniques and provide a comparative study of the methods. In this paper, we conduct a comparative study on 12 selected image fusion metrics over six multiresolution image fusion algorithms for two different fusion schemes and input images with distortion. The analysis can be applied to different image combination algorithms, image processing methods, and over a different choice of metrics that are of use to an image processing expert. The paper relates the results to an image quality measurement based on power spectrum and correlation analysis and serves as a summary of many contemporary techniques for objective assessment of image fusion algorithms. © 2012 IEEE.
Publication date
LanguageEnglish
AffiliationNational Research Council Canada; NRC Institute for Research in Construction
Peer reviewedYes
NPARC number21270086
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Record identifierc4d6a6a9-69dc-47e1-9206-773439370984
Record created2013-12-20
Record modified2016-05-09
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