Paper Title:
Hyperspectral Image Classification Based on Artificial Immune System
  Abstract

The high spectral dimensionality in hyperspectral images causes the reduction of accuracy for common statistical classification methods in these images. Hence the generation and implementation of more complicated methods have gained great importance in this field. One of these methods is the Artificial Immune Systems which is inspired by natural immune system. Despite its great potentiality, it is rarely utilized for spatial sciences and image classification. In this paper a supervised classification algorithm with the application of hyperspectral remote sensing images is proposed. In order to gain better insight into its capability, its accuracy is compared with Artificial Neural Network. The results show better image classification accuracy for the Artificial Immune method.

  Info
Periodical
Chapter
Chapter 2: Microwaves Optics and Image
Edited by
David Wang
Pages
806-812
DOI
10.4028/www.scientific.net/KEM.500.806
Citation
F. Samadzadegan, S. R. Namin, M. A. Rajabi, "Hyperspectral Image Classification Based on Artificial Immune System", Key Engineering Materials, Vol. 500, pp. 806-812, 2012
Online since
January 2012
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Gang Li, Ming Yang, Jian Zhuang
Chapter 9: Others
Abstract:To efficiently mining the classification model, an artificial immune inspired hybrid classification algorithm was put forward by means of...
626
Authors: H.R. Mamatha, Murthy K. Srikanta, K.S. Amrutha, P. Anusha, R. Azeemunisa
Chapter 8: Biomedical Manufacturing
Abstract:Artificial immune system (AIS) based classification approach is relatively new in the field of pattern recognition (PR). The capability of...
900
Authors: Xin Xiao
Chapter 12: Computer-Aided Design and Applications in Industry and Civil Engineering
Abstract:An improved resource limited artificial immune algorithm is proposed, which is applied to the incremental data clustering. The algorithm...
2935