Abstract
This paper presents a new change detection method based on coherence characteristics between channels in Polarimetric Synthetic Aperture Radar (PolSAR) images to change detection. It aims at solving the problem that information sources of change detection measure are limited to image intensity information usually in PolSAR change detection. In this method, by using channel coherence information extracted from polarimetric covariance matrix, and relying on the entropy character, we obtain the similarity factor of improved information sources to change detection. Finally, set a threshold to distinguish the changed targets. Simulations and experiments are carried out to assess and evaluate the performance of the proposed method. A comparison between the proposed and the other well-known change detection methods is shown, which indicates that the proposed method performs well in change detection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cui S, Datcu M, Gueguen L (2011) Information theoretical similarity measure for change detection. In: Joint Urban Remote Sensing Event (JURSE), Munich, 2011. IEEE, pp 69–72
Conradsen K, Nielsen AA, Schou J, Skriver H (2003) A test statistics in the complex Wishart distribution and its application to change detection in polarimetric SAR data. IEEE Trans Geosci Remote Sensing 41:4–19
Moser G, Serpico SB (2009) Unsupervised change detection from multichannel SAR data by Markovian data fusion. IEEE Trans Geosci Remote Sensing 47:2114–2128
Erten E, Reigber A, Ferro-Famil L, Hellwich O (2012) A new coherent similarity measure for temporal multichannel scene characterization. IEEE Trans Geosci Remote Sensing 50:2839–2851
Chaney RD, Burl MC, Novak LM (1990) On the performance of polarimetric target detection algorithms. In: Record of the IEEE Radar conference, Arlington, 1990. IEEE, pp 10–15
Novak LM (2005) Coherent change detection for multi-polarization SAR. In: Conference record of the thirty-ninth Asilomar conference on signals, systems and computers, Pacific Grove, 2005. IEEE, pp 568–573
Irving WW, Owirka GJ, Novak LM (2011) A new model for high-resolution polarimetric SAR clutter data. In: SPIE conference on synthetic aperture Radar, pp 567–576
Goodman NR (2012) Statistical analysis based on a certain multivariate Gaussian distribution. IEEE Trans Geosci Remote Sensing 34:152–177
Gueguen L, Pesaresi M, Ehrlich D, Lu L (2011) Urbanization analysis by mutual information based change detection between SPOT 5 panchromatic images. In: Sixth international workshop on the analysis of multi-temporal remote sensing images (multi-temp), 2011, pp 157–160
Kersten PR, Lee JS, Ainsworth TL (2005) A comparison of change detection statistics in POLSAR images. In: Proceedings of the IEEE international conference on geoscience and remote sensing symposium (IGARSS’05), pp 4836–4839
Acknowledgment
This work is supported by the National Natural Science Foundation of China (No. 61201272).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Huang, Y., Liu, Y., Wu, J., Yang, J. (2015). Similarity Factor Based on Coherence in PolSAR Change Detection. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_24
Download citation
DOI: https://doi.org/10.1007/978-3-319-08991-1_24
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08990-4
Online ISBN: 978-3-319-08991-1
eBook Packages: EngineeringEngineering (R0)