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Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method

Author

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  • Romualdas Bausys

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

  • Giruta Kazakeviciute-Januskeviciene

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

  • Fausto Cavallaro

    (Department of Economics, University of Molise, Via De Sanctis, 86100 Campobasso, Italy)

  • Ana Usovaite

    (Department of Graphical Systems, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania)

Abstract

Nowadays, integrated land management is generally governed by the principles of sustainability. Land use management usually is grounded in satellite image information. The detection and monitoring of areas of interest in satellite images is a difficult task. We propose a new methodology for the adaptive selection of edge detection algorithms using visual features of satellite images and the multi-criteria decision-making (MCDM) method. It is not trivial to select the most appropriate method for the chosen satellite images as there is no proper algorithm for all cases as it depends on many factors, like acquisition and content of the raster images, visual features of real-world images, and humans’ visual perception. The edge detection algorithms were ranked according to their suitability for the appropriate satellite images using the neutrosophic weighted aggregated sum product assessment (WASPAS) method. The results obtained using the created methodology were verified with results acquired in an alternative way—using the edge detection algorithms for specific images. This methodology facilitates the selection of a proper edge detector for the chosen image content.

Suggested Citation

  • Romualdas Bausys & Giruta Kazakeviciute-Januskeviciene & Fausto Cavallaro & Ana Usovaite, 2020. "Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method," Sustainability, MDPI, vol. 12(2), pages 1-24, January.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:2:p:548-:d:307546
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    References listed on IDEAS

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    5. Cavallaro, Fausto & Zavadskas, Edmundas Kazimieras & Streimikiene, Dalia & Mardani, Abbas, 2019. "Assessment of concentrated solar power (CSP) technologies based on a modified intuitionistic fuzzy topsis and trigonometric entropy weights," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 258-270.
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    Cited by:

    1. Phi-Hung Nguyen & Jung-Fa Tsai & Thanh-Tuan Dang & Ming-Hua Lin & Hong-Anh Pham & Kim-Anh Nguyen, 2021. "A Hybrid Spherical Fuzzy MCDM Approach to Prioritize Governmental Intervention Strategies against the COVID-19 Pandemic: A Case Study from Vietnam," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    2. Santautė Venslavienė & Jelena Stankevičienė & Agnė Vaiciukevičiūtė, 2021. "Assessment of Successful Drivers of Crowdfunding Projects Based on Visual Analogue Scale Matrix for Criteria Weighting Method," Mathematics, MDPI, vol. 9(14), pages 1-18, July.

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