Semi-supervised remote sensing image classification methods assessment

Supervised and unsupervised learning are two well disseminated and discussed paradigms which define how image classification techniques extract knowledge about the data. A recent learning paradigm, called semi-supervised, comes to solve some limitations of supervised learning, as the amount of information needed to conduce an appropriated learning process. Different models of semi-supervised learning have been proposed in literature, which ones basically explore statistical or clustering data proprieties. This work presents a simulation study on the performance of some semi-supervised learning models, applied in image classification methods.

[1]  John A. Richards,et al.  Remote Sensing Digital Image Analysis: An Introduction , 1999 .

[2]  Gustavo Camps-Valls,et al.  Semi-Supervised Graph-Based Hyperspectral Image Classification , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Chao Deng,et al.  Multi-class SVM based remote sensing image classification and its semi-supervised improvement scheme , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[4]  S. Kiyasu,et al.  Semi-supervised land cover classification of remotely sensed data using two different types of classifiers , 2009, 2009 ICCAS-SICE.

[5]  James C. Bezdek,et al.  Partially supervised clustering for image segmentation , 1996, Pattern Recognit..

[6]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[7]  Xiaojin Zhu,et al.  Introduction to Semi-Supervised Learning , 2009, Synthesis Lectures on Artificial Intelligence and Machine Learning.

[8]  Vladimir Cherkassky,et al.  The Nature Of Statistical Learning Theory , 1997, IEEE Trans. Neural Networks.

[9]  Alexander Zien,et al.  Semi-Supervised Learning , 2006 .

[10]  Xiaojin Zhu,et al.  --1 CONTENTS , 2006 .

[11]  Lorenzo Bruzzone,et al.  A Novel Transductive SVM for Semisupervised Classification of Remote-Sensing Images , 2006, IEEE Transactions on Geoscience and Remote Sensing.