A review and analysis of backpropagation neural networks for classification of remotely-sensed multi-spectral imagery

Abstract A literature survey and analysis of the use of neural networks for the classification of remotely-sensed multi-spectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding, (2) output encoding and extraction of classes, (3) network architecture, (4) training algorithms, and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its nonparametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsis...

[1]  N. J. Mulder,et al.  Neural Networks Applied To The Classification Of Remotely Sensed Data , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[2]  George F. Hepner,et al.  Artificial neural network classification using a minimal training set - Comparison to conventional supervised classification , 1990 .

[3]  A Comparison Of Neural Network And Expert System Methods For Analysis Of Remotely-sensed Imagery , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.

[4]  Bernard Widrow,et al.  30 years of adaptive neural networks: perceptron, Madaline, and backpropagation , 1990, Proc. IEEE.

[5]  G.G. Wilkinson,et al.  Comparison and visualization of feature space behaviour of statistical and neural classifiers of satellite imagery , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[6]  Richard K. Kiang,et al.  Classification of Remotely Sensed Data Using Ocr-Inspired Neural Network Techniques , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.

[7]  Jeffrey R. Key,et al.  Neural Network VS. Maximum Likelihood Classifications Of Spectral And Textural Features In Visible, Thermal, And Passive Microwave Data , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[8]  G. J. Gibson,et al.  On the decision regions of multilayer perceptrons , 1990, Proc. IEEE.

[9]  G. Pasquariello,et al.  Multispectral classification by a modular neural network architecture , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[10]  Daniel L. Civco,et al.  Artificial Neural Networks for Land-Cover Classification and Mapping , 1993, Int. J. Geogr. Inf. Sci..

[11]  Maureen Caudill,et al.  Neural networks primer, part III , 1988 .

[12]  G. O. Moe,et al.  Multispectral image-processing with a three-layer backpropagation network , 1989, International 1989 Joint Conference on Neural Networks.

[13]  Yi-Chung Rau,et al.  Classification of remote sensing data using partially trained neural network , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[14]  Sigeru Omatu,et al.  Neural network approach to land cover mapping , 1994, IEEE Trans. Geosci. Remote. Sens..

[15]  Zhengkai Liu,et al.  A new approach to pattern recognition of remote sensing image using artificial neural network , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[16]  Robert A. Schowengerdt,et al.  Comparisons of neural networks to standard techniques for image classification and correlation , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[17]  J. Key,et al.  Classification of merged AVHRR and SMMR Arctic data with neural networks , 1989 .

[18]  Richard P. Lippmann,et al.  An introduction to computing with neural nets , 1987 .

[19]  Horst Bischof,et al.  Multispectral classification of Landsat-images using neural networks , 1992, IEEE Trans. Geosci. Remote. Sens..

[20]  George F. Hepner,et al.  Application of an artificial neural network to landcover classification of thematic mapper imagery , 1990 .

[21]  B. Solaiman,et al.  A comparative study of conventional and neural network classification of multispectral data , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[22]  P. Dreyer.  Classification of land cover using optimized neural nets on SPOT data , 1993 .

[23]  Kun-Shan Chen,et al.  A dynamic learning neural network for remote sensing applications , 1994, IEEE Trans. Geosci. Remote. Sens..

[24]  R. Y. Li,et al.  Multi-Spectral Image Classification Using Improved Backpropagation Neural Networks , 1992, [Proceedings] IGARSS '92 International Geoscience and Remote Sensing Symposium.

[25]  P. Swain,et al.  Neural Network Approaches Versus Statistical Methods In Classification Of Multisource Remote Sensing Data , 1990 .

[26]  Z. K. Liu,et al.  Classification of remotely-sensed image data using artificial neural networks , 1991 .

[27]  Jorge Geaga,et al.  Neural net spectral pattern recognition , 1992, Optics & Photonics.

[28]  G.G. Wilkinson,et al.  Integration of neural network and statistical image classification for land cover mapping , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[29]  Richard Lippmann,et al.  Neural Network Classifiers Estimate Bayesian a posteriori Probabilities , 1991, Neural Computation.

[30]  G.G. Wilkinson,et al.  Neural Network Classification Of Multi-date Satellite Imagery , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[31]  Geoffrey E. Hinton,et al.  Learning internal representations by error propagation , 1986 .

[32]  R. Cromp.  Automated extraction of metadata from remotely sensed satellite imagery , 1991 .

[33]  E. Kawaguchi,et al.  Application of neural network approach to classify multi-temporal Landsat images , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[34]  P. D. Heermann,et al.  Classification of multispectral remote sensing data using a back-propagation neural network , 1992, IEEE Trans. Geosci. Remote. Sens..

[35]  Jon Atli Benediktsson,et al.  Classification Of Very High Dimensional Data Using Neural Networks , 1990, 10th Annual International Symposium on Geoscience and Remote Sensing.

[36]  Haruhisa Shimoda,et al.  A classification method using spatial information extracted by neural network , 1993, Proceedings of IGARSS '93 - IEEE International Geoscience and Remote Sensing Symposium.

[37]  Robert A. Schowengerdt,et al.  Techniques for image processing and classification in remote sensing , 1983 .

[38]  Yoh-Han Pao,et al.  Adaptive pattern recognition and neural networks , 1989 .