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Colour transformed clustering-based water body extraction using IRS-1C LISS III image
Author(s) -
Subhash Kulkarni,
Rubina Parveen,
V. D. Mytri
Publication year - 2019
Publication title -
international journal of spatio-temporal data science
Language(s) - English
Resource type - Journals
eISSN - 2399-1283
pISSN - 2399-1275
DOI - 10.1504/ijstds.2019.10018847
Subject(s) - cluster analysis , extraction (chemistry) , image (mathematics) , artificial intelligence , water body , computer science , pattern recognition (psychology) , computer vision , geology , chemistry , chromatography , geotechnical engineering
The algorithm presented in this research article extracts and delineates the water areas using IRS-1C LISS III images. Methods available in the literature are biased with user-defined thresholds. The objective of the proposed algorithm is to provide accurate information about surface water. Initially, the input image is subjected to colour transformation clustering to extract all the similar hydrological characteristics geo-spatial features in the picture. Every cluster is then submitted to surface water detection by considering spectral information. Finally, the surface water bodies are outlined with sharp inter-regional boundaries and made visually vibrant. Thus the task of identification of water bodies is made simple, accurate and easy for the user with satisfactory qualitative analysis. Results obtained are compared with statistics obtained by structural filtering, NDVI method, and spectral segmentation method. The excellent potential surface water areas can be extracted by using the proposed method.

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