Abstract
The shrinking of largest lakes is of worldwide problem. The Aral sea (endorheic lake) lying between Kazakhstan in north and Uzbekistan in south is continuously shrinking since 1960s after rivers that fed into it were diverted by soviet irrigation projects. Satellite image of Aral sea is not much clear to identify the region of water, land and iceland in the image. In this work, the Aral sea satellite image has been taken for the image segmentation. In image segmentation, many steps have been taken like color channel extraction, grayscale conversion, combined (RGB) grayscale conversion, thresholding then thresholding for final red, green and blue color extraction then region of interest segmentation and region of interest inverse of original image for clear human viewing of satellite image in order of water, land and iceland.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Deepika, N.P., Vishnu, K.: Different techniques for satellite image segmentation. In: Online International Conference on Green Engineering and Technologies (IC-GET 2015)
Mukhopadhyay, A.: Interactive approach to multiobjective genetic fuzzy clustering for satellite image segmentation. In: IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics Engineering (UPCON) Indian Institute of Technology (Banaras Hindu University) Varanasi, India, 9–11 Dec 2016
Muangkote, N., Sunat, K., Chiewchanwattana, S.: Multilevel thresholding for satellite image segmentation with moth flame based optimization. In: 13th International Joint Conference on Computer Science and Software Engineering (JCSSE) (2016)
Xing, J., Sieber, R., Kalacska, M.: The challenges of image segmentation in big remotely sensed imagery data. Annals of GIS Taylor & Francis 21 Oct 2014
Ganesan, P., Sajiv, G.: User oriented color space for satellite image segmentation using fuzzy based techniques. In: International Conference on Innovations in information, Embedded and Communication Systems (ICIIECS) (2017)
Awad, M.M.: A new geometric model for clustering highresolution satellite images. International Journal of Remote Sensing Taylor & Francis 02 Apr 2012
Bora, D.J., Gupta, A.K.: AERASCIS: an efficient and robust approach for satellite color image segmentation. In: International Conference on Electrical Power and Energy Systems (ICEPES) Maulana Azad National Institute of Technology, Bhopal, India, 14–16 Dec 2016
Marpu, P.R., Neubert, M., Herold, H., Niemeyer, I.: Enhanced evaluation of image segmentation results. Journal of Spatial Science Taylor & Francis 09 Jul 2010
Pare, S., Bhandari, A.K., Kumar, A., Singh, G.K., Khare, S.: Satellite Image Segmentation based on Different Objective Functions using genetic algorithm: A Comparative Study. IEEE (2015)
Grozavu, N., Rogovschi, N., Cabanes, G., Troya-Galvis, A., Gançarski, P: VHR satellite image segmentation based on topological unsupervised learning. In: 14th IAPR International Conference on Machine Vision Applications (MVA) 18–22 May 2015. Miraikan, Tokyo, Japan
Protschky, V., Seifert, P., Feit, S.: Stop Line Detection Using Satellite-Image Segmentation. IEEE (2015)
Manjula, K.R., Dinesh Kumar, E.: Segmentation of Satellite Image by Enhanced Spatial Clustering Approach. IEEE (2015)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Singh, K.K., Trivedi, S. (2021). Analysis of MATLAB-Based Segmentation and Thresholding of Satellite Image. In: Das, S., Mohanty, M.N. (eds) Advances in Intelligent Computing and Communication. Lecture Notes in Networks and Systems, vol 202. Springer, Singapore. https://doi.org/10.1007/978-981-16-0695-3_19
Download citation
DOI: https://doi.org/10.1007/978-981-16-0695-3_19
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-0694-6
Online ISBN: 978-981-16-0695-3
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)