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Edge Information Based Image Fusion Metrics Using Fractional Order Differentiation and Sigmoidal Functions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18450%2F20%3A50017060" target="_blank" >RIV/62690094:18450/20:50017060 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/abstract/document/9090867/" target="_blank" >https://ieeexplore.ieee.org/abstract/document/9090867/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/ACCESS.2020.2993607" target="_blank" >10.1109/ACCESS.2020.2993607</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Edge Information Based Image Fusion Metrics Using Fractional Order Differentiation and Sigmoidal Functions

  • Original language description

    In recent years, the number of image fusion schemes presented by the research community has increased significantly. Measuring the performance of these schemes is an important issue. In this work, we introduce three quantitative fusion metrics to assess the quality of an image fusion algorithm. The proposed metrics rely on edge information that is obtained using fractional order differentiation. Edge and orientation strengths are fed into three sigmoidal functions separately for estimating the values of three normalized weighted metrics for the fused image corresponding to source images. The experiments on the multi-focus, infrared-visible and medical image fusion pairs demonstrate that the proposed fusion metrics are perceptually meaningful and outperform some of the state-of-the-art metrics.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/EF18_069%2F0010054" target="_blank" >EF18_069/0010054: IT4Neuro(degeneration)</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Access

  • ISSN

    2169-3536

  • e-ISSN

  • Volume of the periodical

    8

  • Issue of the periodical within the volume

    May

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    14

  • Pages from-to

    88385-88398

  • UT code for WoS article

    000538766800004

  • EID of the result in the Scopus database

    2-s2.0-85085204801