Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms
Silvina Pistonesi, Jorge Martinez, Silvia Maria Ojeda, Ronny Vallejos
→ BibTeX
@article{ipol.2018.196,
    title   = {{Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms}},
    author  = {Pistonesi, Silvina and Martinez, Jorge and Ojeda, Silvia Maria and Vallejos, Ronny},
    journal = {{Image Processing On Line}},
    volume  = {8},
    pages   = {345--368},
    year    = {2018},
    doi     = {10.5201/ipol.2018.196},
}
% if your bibliography style doesn't support doi fields:
    note    = {\url{https://doi.org/10.5201/ipol.2018.196}}
published
2018-10-26
reference
Silvina Pistonesi, Jorge Martinez, Silvia Maria Ojeda, and Ronny Vallejos, Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms, Image Processing On Line, 8 (2018), pp. 345–368. https://doi.org/10.5201/ipol.2018.196

Communicated by Miguel Colom
Demo edited by Enric Meinhardt-Llopis, Nelson Monzón

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.

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