Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)

<Previous Article In Volume
Next Article In Volume>

Multifeature Based Satellite Image Segmentation of High Spatial Resolution Remote Sensing Images

Authors
Sujata Gaikwad1, *, Vijaya Musande2
1Department of Computer Science and Engineering, TPCT’s COE, Osmanabad, India
2Department of Computer Science and Engineering, JNEC, Aurangabad, India
*Corresponding author. Email: sujatagaikwad414@gmail.com
Corresponding Author
Sujata Gaikwad
Available Online 10 August 2023.
DOI
10.2991/978-94-6463-196-8_41How to use a DOI?
Keywords
High Spatial Resolution; Satellite Image Segmentation; Remote Sensing
Abstract

With the continuous development of remote sensing technology, the spatial resolution of the image is getting higher and higher and the characteristic information contained in the image is more abundant. High spatial resolution data provides detailed information about the ground for various applications. Methods of Image segmentation become more and more important in the field of remote sensing image analysis. The structural features and texture information are more obvious. The traditional segmentation method based on a single feature of the image can no longer meet the high requirements. In this work, an efficient algorithm is introduced for evaluating segmentation quality. Multifeature based Satellite image segmentation algorithm is proposed to segment the HSR satellite images into different regions based on the properties of multiple features such as color and texture present in the image. The combination of Multifeature information helps to improve an accuracy of segmentation.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
Series
Advances in Intelligent Systems Research
Publication Date
10 August 2023
ISBN
10.2991/978-94-6463-196-8_41
ISSN
1951-6851
DOI
10.2991/978-94-6463-196-8_41How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sujata Gaikwad
AU  - Vijaya Musande
PY  - 2023
DA  - 2023/08/10
TI  - Multifeature Based Satellite Image Segmentation of High Spatial Resolution Remote Sensing Images
BT  - Proceedings of the First International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT 2022)
PB  - Atlantis Press
SP  - 538
EP  - 545
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-196-8_41
DO  - 10.2991/978-94-6463-196-8_41
ID  - Gaikwad2023
ER  -