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Research Article | Open Access

On generalized active contour model in the anisotropic BV space and its application to satellite remote sensing of agricultural territory

Ciro D'Apice1, Peter Kogut2,3, Rosanna Manzo4( )
Dipartimento di Scienze Aziendali-Management and Information Systems, University of Salerno, Via Giovanni Paolo Ⅱ, 132, Fisciano (SA), 84084, Italy
Department of Differential Equations, Oles Honchar Dnipro National University, Gagarin av., 72, 49010 Dnipro, Ukraine
EOS Data Analytics Ukraine, Gagarin av., 103a, Dnipro, Ukraine
Dipartimento di Scienze Politiche e della Comunicazione, University of Salerno, Via Giovanni Paolo Ⅱ, 132, Fisciano (SA), 84084, Italy
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Abstract

Mostly motivated by the crop field classification problem and the automated computational methodology for extracting agricultural crop fields from satellite data, we proposed in a bounded variation (BV) space a new approach to the piecewise smooth approximation of the slope-based vegetation indices and the closely related crop field segmentation problem of multi-band satellite images.

Keywords

optimal segmentation problempiecewise smooth approximationexistence resultoptimality conditionsolevel set methodpartial differential equationactive contour model

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Networks and Heterogeneous Media
Volume 20 Issue 1,
February 2025
Pages 113-142
DOI: 10.3934/nhm.2025008

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Cite this article:
D'Apice C, Kogut P, Manzo R. On generalized active contour model in the anisotropic BV space and its application to satellite remote sensing of agricultural territory. Networks and Heterogeneous Media, 2025, 20(1): 113-142. https://doi.org/10.3934/nhm.2025008

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Received: 17 November 2024
Revised: 01 February 2025
Accepted: 07 February 2025
Published: 15 February 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)