Improving active learning methods using spatial information

Active learning process represents an interesting solution to the problem of training sample collection for the classification of remote sensing images. In this work, we propose a criterion based on the spatial information that can be used in combination with a spectral criterion in order to improve the selection of training samples. Experimental results obtained on a very high resolution image show the effectiveness of regularization in spatial domain and open challenging perspectives for terrain campaigns planning.

[1]  Joydeep Ghosh,et al.  An Active Learning Approach to Hyperspectral Data Classification , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[2]  William J. Emery,et al.  Active Learning Methods for Remote Sensing Image Classification , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[3]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[4]  Johannes R. Sveinsson,et al.  Spectral and spatial classification of hyperspectral data using SVMs and morphological profiles , 2008, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[5]  Farid Melgani,et al.  Support Vector Machine Active Learning Through Significance Space Construction , 2011, IEEE Geoscience and Remote Sensing Letters.

[6]  Greg Schohn,et al.  Less is More: Active Learning with Support Vector Machines , 2000, ICML.

[7]  Farid Melgani,et al.  Automatic Analysis of GPR Images: A Pattern-Recognition Approach , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[8]  F. Melgani,et al.  An Adaptive SVM Nearest Neighbor Classifier for Remotely Sensed Imagery , 2006, 2006 IEEE International Symposium on Geoscience and Remote Sensing.

[9]  William J. Emery,et al.  Classification of Very High Spatial Resolution Imagery Using Mathematical Morphology and Support Vector Machines , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[10]  Gustavo Camps-Valls,et al.  Cluster-based active learning for compact image classification , 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

[11]  Jacob Cohen.  A Coefficient of Agreement for Nominal Scales , 1960 .

[12]  Sankar K. Pal,et al.  Segmentation of multispectral remote sensing images using active support vector machines , 2004, Pattern Recognit. Lett..