A comparative study of RIFCM with other related algorithms from their suitability in analysis of satellite images using other supporting techniques
Abstract
Purpose
The purpose of this paper is to provide a way to analyze satellite images using various clustering algorithms and refined bitplane methods with other supporting techniques to prove the superiority of RIFCM.
Design/methodology/approach
A comparative study has been carried out using RIFCM with other related algorithms from their suitability in analysis of satellite images with other supporting techniques which segments the images for further process for the benefit of societal problems. Four images were selected dealing with hills, freshwater, freshwatervally and drought satellite images.
Findings
The superiority of the proposed algorithm, RIFCM with refined bitplane towards other clustering techniques with other supporting methods clustering, has been found and as such the comparison, has been made by applying four metrics (Otsu (Max-Min), PSNR and RMSE (40%-60%-Min-Max), histogram analysis (Max-Max), DB index and D index (Max-Min)) and proved that the RIFCM algorithm with refined bitplane yielded robust results with efficient performance, reduction in the metrics and time complexity of depth computation of satellite images for further process of an image.
Practical implications
For better clustering of satellite images like lands, hills, freshwater, freshwatervalley, drought, etc. of satellite images is an achievement.
Originality/value
The existing system extends the novel framework to provide a more explicit way to analyze an image by removing distortions with refined bitplane slicing using the proposed algorithm of rough intuitionistic fuzzy c-means to show the superiority of RIFCM.
Keywords
Acknowledgements
The authors would be thankful for the management for providing them the opportunity to carry out this research.
Citation
Purushotham, S. and Tripathy, B. (2014), "A comparative study of RIFCM with other related algorithms from their suitability in analysis of satellite images using other supporting techniques", Kybernetes, Vol. 43 No. 1, pp. 53-81. https://doi.org/10.1108/K-12-2012-0126
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited