Indian river watershed image analysis using fuzzy-CA hybrid approach

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKapitel samlingsverk

Abstract

Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automata model based on fuzzy segmentations. This approach detects the overlapping regions in remote sensing images by uncertainties using fuzzy set membership values. As a discrete, dynamical system, cellular automaton explores uniformly interconnected cells with states. In the second phase of our method, we utilize a 2-dimensional cellular automata to prioritize allocations of mixed pixels among overlapping land cover areas. We experiment our method on Indian Ajoy river watershed area. The clustered regions are compared with well-known FCM and K-Means methods and also with the ground truth knowledge. The results show the superiority of our new method.

Detaljer

Författare
Externa organisationer
  • Government College of Engineering & Leather Technology, Kolkata
  • Jadavpur University
Originalspråkengelska
Titel på värdpublikationEnvironmental Information Systems
Undertitel på gästpublikationConcepts, Methodologies, Tools, and Applications
FörlagIGI Global
Sidor1148-1162
Volym3
ISBN (elektroniskt)9781522570349
ISBN (tryckt)9781522570332
StatusPublished - 2018 jan 1
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa