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                        {
                            "codemeta:affiliation": "Departamento de Matem\u00e1tica, Universidad Nacional del Sur, Argentina and Facultad Regional Bah\u00eda Blanca, Universidad Tecnol\u00f3gica Nacional, Argentina",
                            "codemeta:name": "Silvina Pistonesi"
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                            "codemeta:affiliation": "Departamento de Matem\u00e1tica, Universidad Nacional del Sur, Argentina",
                            "codemeta:name": "Jorge Martinez"
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                            "codemeta:name": "Silvia Maria Ojeda"
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                        "codemeta:name": "Image Processing On Line (IPOL)",
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                        "codemeta:abstract": "The wide use of image fusion techniques in different fields such as medical diagnostics, digital camera vision, military and surveillance applications, among others, has motivated the development of various image quality fusion metrics, in order to evaluate them. In this paper, we study and implement the algorithms of non-reference image structural similarity based metrics for fusion assessment: Piella's metric, Cvejic's metric, Yang's metric, and Codispersion Fusion Quality metric. We conduct the comparative experiment of the selected image fusion metrics over four multiresolution image fusion algorithms, performed on different pairs of images used in different applications.",
                        "codemeta:identifier": "https://doi.org/10.5201/ipol.2018.196",
                        "codemeta:name": "Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms",
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                    "codemeta:releaseNotes": "This code implements the algorithm(s) published in the IPOL paper \"Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms\"",
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