V. S. Sangeetha, S. Revathy, C. Sahithya, A. Seethalakshmi, Sri Ramakrishna Engineering College, Coimbatore, Tamilnadu, India.
DOI : 01.0401/ijaict.2015.12.05
International Journal of Advanced Information and Communication Technology
Received On : June 16, 2018
Revised On : July 18, 2018
Accepted On : August 11, 2018
Published On : September 05, 2018
Volume 05, Issue 09
Pages : 934-940
Abstract
Hyperspectral image classification with limited number of labeled pixels is a challenging task. hyperspectral image is sampled from hundreds or thousands of contiguous and narrow spectral bands by hyperspectral sensors.Many applications involving hyperspectral image analysis are in need of a semantic classification task i.e., partition and label the hyperspectral image into different semantic regions, such as trees and beaches, which remains to be a challenging problem. We propose a hyperspectral image classification framework by a multilayer graph based learning using labview.This multilayer graph is composed of a several bilayer layer of simple graph as well as a layer of hypergraph, which effectively exploits the underlying structure of the data. In the first-layer, a simple graph is constructed, where each vertex in the graph denotes one pixel and the similarity among vertices is determined by the feature based pairwise pixel distances.Learning is conducted on this layer to estimate the connectivity relationship among pixels.In the second-layer, a hypergraph structure is constructed, where each vertex denotes one pixel and the hyperedges are generated by using the neighborhood relationship produced from the first-layer.Here we use kernel nearest neighbour technique for distance calculation in second layer .Semi-supervised learning is conducted on the hypergraph structure to estimate the pixel labels to achieve hyperspectral image classification. Our experiments on three datasets validated the effectiveness of the proposed method, which compared favorably with state-of-the-art.
Keywords
Hyperspectral imaging, image classification, graph based learning, hypergraph learning.
Cite this article
V. S. Sangeetha, S. Revathy, C. Sahithya, A. Seethalakshmi, “Hyperspectral Image Classification through Multilayer Graph Based Learning” INTERNATIONAL JOURNAL OF ADVANCED INFORMATION AND COMMUNICATION TECHNOLOGY, pp.934-940, September 05, 2018.
Copyright
© 2018 V. S. Sangeetha, S. Revathy, C. Sahithya, A. Seethalakshmi. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.