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321064

Current Trends and Future Directions in Sea-Land Segmentation for Remote Sensing Images

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Last updated: 05 Jan 2025

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Abstract

 Nowadays, sea-land segmentation for remote sensing images has a valuable role in water resources monitoring, maritime safety, and coastal zones management. However, it has faced many challenges such as the complicated distribution of land area, noise, poor contrast between sea and land regions, different weather conditions, the development of sensors, and high-resolution images provide more information. Consequently, there are considerable efforts have been made to develop various methods to overcome these challenges. Therefore, this paper introduces the description of the main steps of the sea-land segmentation procedure and the main characteristics of each step. Also, the paper focuses on the taxonomy of the current sea-land segmentation methods. These methods are broadly categorized into six main groups namely thresholding-based methods, region-based methods, energy minimization-based methods, machine learning-based methods, watershed transformation-based methods, and hybrid methods. Finally, this paper also shows and discusses the common challenges which are facing the sea-land segmentation. Besides, the paper introduces promising future research directions in the sea-land segmentation field. 

DOI

10.21608/mjcis.2019.321064

Keywords

Sea-land segmentation, Remote Sensing, Coastline/shoreline Extraction, Machine Learning, Energy Minimization

Authors

First Name

Eman

Last Name

Elkhateeb

MiddleName

-

Affiliation

Faculty of computers and information systems, I.T dep. Mansoura University, Egypt

Email

-

City

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Orcid

-

First Name

Nagham

Last Name

Mekky

MiddleName

-

Affiliation

Faculty of computers and information systems, I.T dep. Mansoura University, Egypt

Email

-

City

-

Orcid

-

First Name

Ahmed

Last Name

Atwan

MiddleName

-

Affiliation

Faculty of computers and information systems, I.T dep. Mansoura University, Egypt

Email

atwan@mans.edu.eg

City

-

Orcid

-

First Name

Hassan

Last Name

Soliman

MiddleName

-

Affiliation

Faculty of computers and information systems, I.T dep. Mansoura University, Egypt

Email

hsoliman@mans.edu.eg

City

-

Orcid

-

Volume

15

Article Issue

2

Related Issue

43866

Issue Date

2019-12-01

Receive Date

2023-10-11

Publish Date

2019-12-01

Page Start

11

Page End

26

Print ISSN

2090-1666

Online ISSN

2090-1674

Article File

MJCIS_Volume 15_Issue 2_Pages 11-26.pdf

PDF . 1.8MB

Link

https://mjcis.journals.ekb.eg/article_321064.html

Detail API

https://mjcis.journals.ekb.eg/service?article_code=321064

Order

321,064

Type

Original Research Articles.

Type Code

1,784

Publication Type

Journal

Publication Title

Mansoura Journal for Computer and Information Sciences

Publication Link

https://mjcis.journals.ekb.eg/

MainTitle

Current Trends and Future Directions in Sea-Land Segmentation for Remote Sensing Images

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Type

Article

Created At

28 Dec 2024