Volume 7 Issue 2 - July 2016

  • 1. Unsupervised classification of remote sensing images using k-means algorithm

    Authors : Neerugattvaripally Vishwanath, Badavath Ramesh, P Sreenuvasa Rao

    Pages : 548-552

    DOI : http://dx.doi.org/10.21172/1.72.584

    Keywords : Clustering algorithm, Image Classification, Image Segmentation

    Abstract :

    Image classification techniques are used in the field of remote sensing to cluster pixels in order to represent land cover features. Land cover could be classified into forested, urban, agricultural and other type of land. In unsupervised classification, the user identifies the number of clusters to generate and the bands which has to be used. Using this information clusters are generated from the image. In this paper, we propose a clustering algorithm which can achieve the robustness required in unsupervised classification of remote sensing images. The experimental results prove that the desired algorithm is very effective in producing desired clusters of the given data sets as well as diagnosis. The algorithm is very much useful in classification as well as extraction of regions in satellite images.

    Citing this Journal Article :

    Neerugattvaripally Vishwanath, Badavath Ramesh, P Sreenuvasa Rao , "Unsupervised classification of remote sensing images using k-means algorithm", https://www.ijltet.org/journal_details.php?id=906&j_id=3291, Volume 7 Issue 2 - July 2016, 548-552, #ijltetorg