Call for Paper - October 2019 Edition
IJCA solicits original research papers for the October 2019 Edition. Last date of manuscript submission is September 20, 2019. Read More

Remote Sensing Image Classification using Back Propogation

Print
PDF
IJCA Proceedings on National Conference on Advances in Communication and Computing
© 2014 by IJCA Journal
NCACC 2014 - Number 2
Year of Publication: 2014
Authors:
Shah Kehul
More S A

Shah Kehul and More S A. Article: Remote Sensing Image Classification using Back Propogation. IJCA Proceedings on National Conference on Advances in Communication and Computing NCACC(2):9-11, December 2014. Full text available. BibTeX

@article{key:article,
	author = {Shah Kehul and More S A},
	title = {Article: Remote Sensing Image Classification using Back Propogation},
	journal = {IJCA Proceedings on National Conference on Advances in Communication and Computing},
	year = {2014},
	volume = {NCACC},
	number = {2},
	pages = {9-11},
	month = {December},
	note = {Full text available}
}

Abstract

The resolution of remote sensing images increase every day . Most of the existing methods is used the same method for years. The existing method does not provide satisfactory result. The aim is to develop an artificial neural network based on classification method consists of segmentation and classification . Segmentation followed by K-Means method and then classification performed with back propagation neural network which provide accuracy and satisfactory result compare to the other method.

References

  • G. M. and Mathur, A ``Toward intelligent training of supervised image classification: directing training data acquisition for SVM classification "RemoteSensing of Environment 93, pp. 107-117,2004
  • Benediktsson, J. A. , and Sveinsson, J. R. " Feature extraction for multi-sourcedata classification with artificial neural networks",International Journal of Remote Sensing 18, 727-740,1997
  • Guoqiang Peter Zhang. ``Neural networks for classification : a Survey",IEEE Transaction on Systems, Man and Cybernetics-Part C : Application and Re-views, 30(4) : 451-462,2000
  • Qing Liu, GuangminWu, Jianming Chen ,``Interpretation Artifcial Neural Network in Remote Sensing Image Classifcation", IEEE transaction 978-1-4673-0875,2012
  • P. M. Atkinson and A. R. L. Tatnal. ``Introduction neural networks in remote sensing",Remote Sensing 18(4) : 699-709, 1997.
  • Atkinson, P. D. and Tatnall, R. L. ," Neural networks in remote sensing"Int. J. Remote Sensing 18(4), 699-709,1997
  • G. Dong & M. Xie, ``Color Clustering & Learning for Image Segmentation Based on Neural Networks", IEEE, Vol. 16, No. 4 Pp. 925-936.
  • Howard Demuth, Mark Beale and Martin Hagan. ``Neural network ToolboxTM6 User's Guide",2010
  • Jum-Ding Sun andYuam Ma ``Image Classification Based on Texture and Improved BP Network",ISECS pp098-100,2010
  • F. Qiu and J. R. Jensen ``Open the black box of neural networks for remote sensing image classification", Remote Sensing 25(9) : 1749- 1768,2004
  • Shi Y, Han L Q and Lian X Q ``Design,Method and Cases Analysis of Neural Networks" ,Beijing University of Posts and Telecommunications Press : 1-2,25-29, 77-82, 113-114,147-148 ,2009
  • Dean, A. M and Smith, G. M. , ``An evaluation of per parcel land cover mapping using maximum likelihood class probabilities", International Journal of Remote Sensing 24 (14), pp. 2905-2920 ,2003.
  • Z. W. Xu. ``Introducing stored-grain pest image retrieval based on BP neural network",Journal of the Chinese cereals and oils association,vol. 25, 2010, pp. 103-106.
  • R. L. Ruan. ``Application of genetic algorithm in artificial neural network weights optimizing", Journal of xianning university, vol. 2, 2005, pp. 4951.
  • C. F. Luo, Z. J. Liu,C. Y. Wang,Z. Niu `Optimized BP neural network classifier based on genetic algorithm for land cover classification using remotely-sensed data",Transactions of the Chinese society of agricultural engineering, vol. 29, 2006, pp. 133137.
  • Campbell, J. B. ,``Introduction to Remote Sensing 3rd Edition"The Guilford Press, NewYork, USA ,2002
  • Benitez, J. M. , Castro, J. L. , and Requena, " An artificial neural networks black boxes",IEEE Transactions on Neural Networks 8, 1156-1164,1996