Fuzzy texture characterization of urban environments by SAR data

The authors present a texture-base approach to the classification of SAR images recorded over urban environments. In particular, they explore the use of some co-occurrence measures and the wavelet frame decomposition, to investigate if there is an advantage, and where, in using these tools. They found that the correct classification rates are only partially increased by using these additional information, with a slight preference for texture analysis through the co-occurence matrix. These considerations are validated by analyzing polarimetric SAR images recorded over Los Angeles by the AIRSAR sensor.

[1]  F. Parmiggiani,et al.  An investigation of the textural characteristics associated with gray level cooccurrence matrix statistical parameters , 1995, IEEE Transactions on Geoscience and Remote Sensing.

[2]  M. A. Shaban,et al.  Textural classification of high resolution digital satellite imagery , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).

[3]  F. Parmiggiani,et al.  Urban Area Classification By Multispectral SPOT Images , 1990 .

[4]  Robert M. Haralick,et al.  Textural Features for Image Classification , 1973, IEEE Trans. Syst. Man Cybern..

[5]  Michael Unser,et al.  Texture classification and segmentation using wavelet frames , 1995, IEEE Trans. Image Process..

[6]  Paolo Gamba,et al.  Classification of urban environments in SAR images: a fuzzy clustering perspective , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).