Multispectral Satellite Color Image Segmentation Using Fuzzy Based Innovative Approach

Authors(3) :-Dr. Anil Kumar Gupta, Dibya Jyoti Bora, Fayaz Ahmad Khan

Multispectral satellite color images need special treatment for object-based classification like segmentation. Traditional algorithms are not efficient enough for performing segmentation of such high-resolution images. So, an innovative approach for segmentation of multispectral color images is proposed in this paper. The proposed approach consists of two phases. In the first phase, the preprocessing of the selected bands is taken place for noise removal and contrast enhancement. In the second phase, fuzzy segmentation of the enhanced version obtained in the first phase is carried out. The results found are quite promising and comparatively better than the other state of the art algorithms.

Authors and Affiliations

Dr. Anil Kumar Gupta
HOD, Department of Computer Science & Applications, Barkatullah University, Bhopal, Madhya Pradesh, India
Dibya Jyoti Bora
Senior IT Faculty, School of Computing Sciences, Kaziranga University, Jorhat , Assam, India
Fayaz Ahmad Khan
Guest Faculty, Department of Computer Science & Applications, Barkatullah University, Bhopal, Madhya Pradesh, India

Color Image Segmentation, CLAHE, Median filter, Multispectral satellite image, RGB, HSV Color Space, FCM Algorithm

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Publication Details

Published in : Volume 3 | Issue 1 | January-February 2018
Date of Publication : 2018-02-28
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 968-975
Manuscript Number : CSEIT1831231
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Dr. Anil Kumar Gupta, Dibya Jyoti Bora, Fayaz Ahmad Khan , "Multispectral Satellite Color Image Segmentation Using Fuzzy Based Innovative Approach", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.968-975, January-February-2018.
Journal URL : http://ijsrcseit.com/CSEIT1831231

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