Using Image Quality Assessment (IQA) Databases to Provide an Appraisal of the Ability of the Feature Selective Validation Method (FSV) to Compare 2-dimensional Datasets

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dc.contributor.author Zhang, Gang en
dc.contributor.author Orlandi, Antonio en
dc.contributor.author Duffy, A.P. en
dc.date.accessioned 2018-01-03T09:27:38Z
dc.date.available 2018-01-03T09:27:38Z
dc.date.issued 2017-11-16
dc.identifier.citation Gang, Z., Orlandi, A. and Duffy, A.P. (2017) Using Image Quality Assessment (IQA) Databases to Provide an Appraisal of the Ability of the Feature Selective Validation Method (FSV) to Compare 2-dimensional Datasets. IEEE Transactions on Electromagnetic Compatibility, en
dc.identifier.issn 0018-9375
dc.identifier.uri http://hdl.handle.net/2086/15048
dc.description The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. en
dc.description.abstract This paper investigates the strengths and drawbacks of the recently developed FSV-2D method. Considering that a subjective benchmark for the validation of 2-dimensional computational electromagnetics data is not available, five datasets with subjective scores, commonly used in image quality assessment, are used. It is found that the FSV-2D prediction is influenced by image type and distortion type. Encouraged by the assessment results, eight parameters of the FSV-2D method are optimized by use of genetic algorithms. It is shown that the optimized FSV-2D method provides better correlation with subjective scores. Good agreement with theoretical analysis for computational electromagnetic data further validates the proposed approach. en
dc.language.iso en en
dc.publisher IEEE en
dc.subject Feature Selective Validation en
dc.subject Validation en
dc.subject Modeling en
dc.subject Comparisons en
dc.title Using Image Quality Assessment (IQA) Databases to Provide an Appraisal of the Ability of the Feature Selective Validation Method (FSV) to Compare 2-dimensional Datasets en
dc.type Article en
dc.researchgroup Engineering and Physical Sciences Institute (EPsi) en
dc.funder N/A en
dc.projectid N/A en
dc.cclicence CC-BY-NC en
dc.date.acceptance 2017-11-16 en


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