Hybrid rough-PSO approach in remote sensing imagery analysis

Forskningsoutput: Kapitel i bok/rapport/Conference proceedingKapitel samlingsverk

Abstract

Pixel classification among overlapping land cover regions in remote sensing imagery is a very challenging task. Detection of uncertainty and vagueness are always the key features for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of rough set theory and particle swarm optimization methods. Rough set theory deals with incompleteness and vagueness among data, which property may be utilized for detecting arbitrarily shaped and sized clusters in satellite images. To enable fast automatic clustering of multispectral remote sensing imagery, in this article, we propose a rough set-based heuristical decision rule generation algorithm. For rough-set-theoretic decision rule generation, each cluster is classified using heuristically searched optimal reducts to overcome overlapping cluster problem. This proposed unsupervised algorithm is able to identify clusters utilizing particle swarm optimization based on rough set generated membership values. This approach addresses the overlapping regions in remote sensing images by uncertainties using rough set generated membership values. Particle swarm optimization is a population-based stochastic optimization technique, inspired from the social behavior of bird flock. Therefore, to predict pixel classification of remote sensing imagery, we propose a particle swarm optimization-based membership correction approach over rough set-based initial decision rule generation. We demonstrate our algorithm for segmenting a LANDSAT image of the catchment area of Ajoy River. The newly developed algorithm is compared with fuzzy C-means and K-means algorithms. The new algorithm generated clustered regions are verified with the available ground truth knowledge. The validity analysis is performed to demonstrate the superior performance of our new algorithms with K-means and fuzzy C-means algorithms.

Detaljer

Författare
Externa organisationer
  • Government College of Engineering & Leather Technology, Kolkata
  • Jadavpur University
Forskningsområden

Nyckelord

Originalspråkengelska
Titel på värdpublikationHybrid Soft Computing Approaches
Undertitel på gästpublikationResearch and Applications
FörlagSpringer
Sidor305-327
Volym611
ISBN (elektroniskt)9788132225447
ISBN (tryckt)9788132225430
StatusPublished - 2015 aug 21
PublikationskategoriForskning
Peer review utfördJa
Externt publiceradJa