Unsupervised Change Detection From Multichannel SAR Data by Markovian Data Fusion

In applications related to environmental monitoring and disaster management, multichannel synthetic aperture radar (SAR) data present a great potential, owing both to their insensitivity to atmospheric and Sun-illumination conditions and to the improved discrimination capability they may provide as compared with single-channel SAR. However, exploiting this potential requires accurate and automatic techniques to generate change maps from (multichannel) SAR images acquired over the same geographic region in different polarizations or at different frequencies at different times. In this paper, a contextual unsupervised change-detection technique (based on a data-fusion approach) is proposed for two-date multichannel SAR images. Each SAR channel is modeled as a distinct information source, and a Markovian approach to data fusion is adopted. A Markov random field model is introduced that combines together the information conveyed by each SAR channel and the spatial contextual information concerning the correlation among neighboring pixels and formulated by using ldquoenergy functions.rdquo In order to address the task of the estimation of the model parameters, the expectation-maximization algorithm is combined with the recently proposed ldquomethod of log-cumulants.rdquo The proposed technique was experimentally validated with semisimulated multipolarization and multifrequency data and with real SIR-C/XSAR images.

[1]  Pierfrancesco Lombardo,et al.  A new maximum-likelihood joint segmentation technique for multitemporal SAR and multiband optical images , 2003, IEEE Trans. Geosci. Remote. Sens..

[2]  Qiong Jackson,et al.  Adaptive Bayesian contextual classification based on Markov random fields , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[3]  S. Quegan,et al.  Understanding Synthetic Aperture Radar Images , 1998 .

[4]  Gabriele Moser,et al.  Unsupervised change detection methods for remote sensing images , 2002, SPIE Remote Sensing.

[5]  Salah Bourennane,et al.  Unsupervised change detection on SAR images using fuzzy hidden Markov chains , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[6]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Paolo Gamba,et al.  Change Detection of Multitemporal SAR Data in Urban Areas Combining Feature-Based and Pixel-Based Techniques , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[8]  Francesca Bovolo,et al.  A detail-preserving scale-driven approach to change detection in multitemporal SAR images , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[9]  Xavier Descombes,et al.  Estimating Gaussian Markov random field parameters in a nonstationary framework: application to remote sensing imaging , 1999, IEEE Trans. Image Process..

[10]  Jorma Laaksonen,et al.  Detecting changes in polarimetric SAR data with content-based image retrieval , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[11]  Gabriele Moser,et al.  Unsupervised change detection by multichannel SAR data fusion , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[12]  Josef Kittler,et al.  Minimum error thresholding , 1986, Pattern Recognit..

[13]  A. Gualtierotti.  H. L. Van Trees, Detection, Estimation, and Modulation Theory, , 1976 .

[14]  Ashbindu Singh,et al.  Review Article Digital change detection techniques using remotely-sensed data , 1989 .

[15]  Jon Atli Benediktsson,et al.  Consensus theoretic classification methods , 1992, IEEE Trans. Syst. Man Cybern..

[16]  Keinosuke Fukunaga,et al.  Introduction to statistical pattern recognition (2nd ed.) , 1990 .

[17]  Lorenzo Bruzzone,et al.  An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[18]  J.S. Lee,et al.  A comparison of change detection statistics in POLSAR images , 2005, Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05..

[19]  R. G. White,et al.  Change detection in SAR imagery , 1990 .

[20]  Gilles Celeux,et al.  EM procedures using mean field-like approximations for Markov model-based image segmentation , 2003, Pattern Recognit..

[21]  Jordi Inglada,et al.  A New Statistical Similarity Measure for Change Detection in Multitemporal SAR Images and Its Extension to Multiscale Change Analysis , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Kun-Shan Chen,et al.  Change detections from sar images for damage estimation based on a spatial chaotic model , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[23]  R. Redner,et al.  Mixture densities, maximum likelihood, and the EM algorithm , 1984 .

[24]  Farid Melgani.  Classification Of Multitemporal Remote-Sensing Images By A Fuzzy Fusion Of Spectral And Spatio-Temporal Contextual Information , 2004, Int. J. Pattern Recognit. Artif. Intell..

[25]  A. Lopes,et al.  A statistical and geometrical edge detector for SAR images , 1988 .

[26]  Lorenzo Bruzzone,et al.  Automatic identification of the number and values of decision thresholds in the log-ratio image for change detection in SAR images , 2006, IEEE Geoscience and Remote Sensing Letters.

[27]  Gabriele Moser,et al.  Dictionary-based stochastic expectation-maximization for SAR amplitude probability density function estimation , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[28]  Jean-Marie Nicolas.  1 - Introduction aux Statistiques de deuxième espèce : applications des Logs-moments et des Logs-cumulants à l'analyse des lois d'images radar , 2002 .

[29]  Geoffrey G. Hazel.  Object-level change detection in spectral imagery , 2001, IEEE Trans. Geosci. Remote. Sens..

[30]  Mehrdad Soumekh,et al.  Signal subspace change detection in averaged multilook SAR imagery , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[31]  New York Dover,et al.  ON THE CONVERGENCE PROPERTIES OF THE EM ALGORITHM , 1983 .

[32]  Keinosuke Fukunaga,et al.  Introduction to Statistical Pattern Recognition , 1972 .

[33]  Matthieu Molinier,et al.  Comparison and evaluation of polarimetric change detection techniques in aerial SAR data , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[34]  Donald Geman,et al.  Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .

[35]  Lorenzo Bruzzone,et al.  A neural-statistical approach to multitemporal and multisource remote-sensing image classification , 1999, IEEE Trans. Geosci. Remote. Sens..

[36]  Jon Atli Benediktsson,et al.  Classification of multisource and hyperspectral data based on decision fusion , 1999, IEEE Trans. Geosci. Remote. Sens..

[37]  Florian Siegert,et al.  The 1998 Forest Fires in East Kalimantan (Indonesia): A Quantitative Evaluation Using High Resolution, Multitemporal ERS-2 SAR Images and NOAA-AVHRR Hotspot Data , 2000 .

[38]  Gabriele Moser,et al.  SAR amplitude probability density function estimation based on a generalized Gaussian model , 2006, IEEE Transactions on Image Processing.

[39]  Lorenzo Bruzzone,et al.  Change detection in multitemporal SAR images based on generalized Gaussian distribution and EM algorithm , 2004, SPIE Remote Sensing.

[40]  Lorenzo Bruzzone,et al.  An experimental comparison of neural and statistical non-parametric algorithms for supervised classification of remote-sensing images , 1996, Pattern Recognit. Lett..

[41]  Sebastiano B. Serpico,et al.  High resolution COSMO/SkyMed SAR data analysis for civil protection from flooding events , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[42]  William H. Press,et al.  Numerical recipes in C , 2002 .

[43]  Anil K. Jain,et al.  Random field models in image analysis , 1989 .

[44]  Pierfrancesco Lombardo,et al.  Maximum likelihood signal processing techniques to detect a step pattern of change in multitemporal SAR images , 2002, IEEE Trans. Geosci. Remote. Sens..

[45]  Stéphane Derrode,et al.  SAR image change detection using distance between distributions of classes , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[46]  Henri Maître,et al.  A new statistical model for Markovian classification of urban areas in high-resolution SAR images , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[47]  Jean-Marie Nicolas,et al.  Application of log-cumulants to the detection of spatiotemporal discontinuities in multitemporal SAR images , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[48]  Farid Melgani,et al.  A statistical approach to the fusion of spectral and spatio-temporal contextual information for the classification of remote-sensing images , 2002, Pattern Recognit. Lett..

[49]  Muhtar Qong,et al.  Polarization state conformation and its application to change detection in polarimetric SAR data , 2004, IEEE Geosci. Remote. Sens. Lett..

[50]  Lars M. H. Ulander,et al.  Detection of storm-damaged forested areas using airborne CARABAS-II VHF SAR image data , 2002, IEEE Trans. Geosci. Remote. Sens..

[51]  Francesca Bovolo,et al.  A Split-Based Approach to Unsupervised Change Detection in Large-Size Multitemporal Images: Application to Tsunami-Damage Assessment , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[52]  Qiong Jackson,et al.  An adaptive classifier design for high-dimensional data analysis with a limited training data set , 2001, IEEE Trans. Geosci. Remote. Sens..

[53]  Gabriele Moser,et al.  Generalized minimum-error thresholding for unsupervised change detection from SAR amplitude imagery , 2006, IEEE Trans. Geosci. Remote. Sens..

[54]  Anil K. Jain,et al.  A Markov random field model for classification of multisource satellite imagery , 1996, IEEE Trans. Geosci. Remote. Sens..

[55]  X. Lia,et al.  Multitemporal SAR images for monitoring cultivation systems using case-based reasoning , 2004 .

[56]  Gabriele Moser,et al.  MRF-Based Remote-Sensing Image Classification with Automatic Model Parameter Estimation , 2006 .

[57]  Gabriele Moser,et al.  Conditional Copulas for Change Detection in Heterogeneous Remote Sensing Images , 2008, IEEE Transactions on Geoscience and Remote Sensing.

[58]  M. Dobson,et al.  The use of Imaging radars for ecological applications : A review , 1997 .

[59]  Jakob J. van Zyl,et al.  Change detection techniques for ERS-1 SAR data , 1993, IEEE Trans. Geosci. Remote. Sens..

[60]  Luciano Alparone,et al.  Robust change analysis of SAR data through information-theoretic multitemporal features , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[61]  Wolfgang Dierking,et al.  Change detection for thematic mapping by means of airborne multitemporal polarimetric SAR imagery , 2002, IEEE Trans. Geosci. Remote. Sens..

[62]  I. N. Sneddon.  The use of integral transforms , 1972 .

[63]  David A. Landgrebe,et al.  Signal Theory Methods in Multispectral Remote Sensing , 2003 .

[64]  Gabriele Moser,et al.  Unsupervised Change Detection From Multichannel SAR Images , 2007, IEEE Geoscience and Remote Sensing Letters.

[65]  W. Rudin.  Principles of mathematical analysis , 1964 .

[66]  Knut Conradsen,et al.  A test statistic in the complex Wishart distribution and its application to change detection in polarimetric SAR data , 2003, IEEE Trans. Geosci. Remote. Sens..

[67]  Johannes R. Sveinsson,et al.  Hybrid consensus theoretic classification , 1996, IGARSS '96. 1996 International Geoscience and Remote Sensing Symposium.

[68]  Jordi Inglada,et al.  Change detection on SAR images by using a parametric estimation of the Kullback-Leibler divergence , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[69]  Lorenzo Bruzzone,et al.  A context-sensitive Bayesian technique for the partially supervised classification of multitemporal images , 2005, IEEE Geoscience and Remote Sensing Letters.