Change Detection and Image Time Series Analysis 2. Группа авторов
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Название: Change Detection and Image Time Series Analysis 2

Автор: Группа авторов

Издательство: John Wiley & Sons Limited

Жанр: Программы

Серия:

isbn: 9781119882282

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СКАЧАТЬ (2011). Robust multi-sensor classification via joint sparse representation. International Conference on Information Fusion.

      Pan, S., Wu, J., Zhu, X., Zhang, C., Philip, S.Y. (2015). Joint structure feature exploration and regularization for multi-task graph classification. IEEE Transactions on Knowledge and Data Engineering, 28(3), 715–728.

      Pérez, P. (1993). Champs markoviens et analyse multirésolution de l’image : application à l’analyse du mouvement. PhD Thesis, University of Rennes 1, France.

      Piella, G. (2003). Adaptive wavelets and their applications to image fusion and compression. Thesis, PhD Thesis, University of Amsterdam.

      Pohl, C. and van Genderen, J. (1998). Review article – Multisensor image fusion in remote sensing: Concepts, methods and applications. International Journal of Remote Sensing, 19(5), 823–854.

      Pohl, C. and van Genderen, J. (2014). Remote sensing image fusion: An update in the context of digital earth. International Journal of Digital Earth, 7(2), 158–172.

      Prendes, J. (2015). New statistical modeling of multi-sensor images with application to change detection. Thesis, PhD Thesis, Université Paris-Sud, France.

      Roberts, J., van Aardt, J., Ahmed, F. (2008). Assessment of image fusion procedures using entropy, image quality, and multispectral classification. Journal of Applied Remote Sensing, 2(1), 023522 [Online]. Available at: https://doi.org/10.1117/1.2945910.

      Serpico, S., Dellepiane, S., Boni, G., Moser, G., Angiati, E., Rudari, R. (2012). Information extraction from remote sensing images for flood monitoring and damage evaluation. Proceedings of the IEEE, 100(10), 2946–2970.

      Shah, V., Younan, N., King, R. (2008). An efficient pan-sharpening method via a combined adaptive PCA approach and contourlets. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1323–1335.

      Storvik, B., Storvik, G., Fjortoft, R. (2009). On the combination of multisensor data using meta-Gaussian distributions. IEEE Transactions on Geoscience and Remote Sensing, 47(7), 2372–2379.

      Stroppiana, D., Azar, R., Calo, F., Pepe, A., Imperatore, P., Boschetti, M., Silva, J., Brivio, P., Lanari, R. (2015). Remote sensing of burned area: A fuzzy-based framework for joint processing of optical and microwave data. IEEE Geoscience and Remote Sensing Symposium (IGARSS), pp. 1409–1412.

      Ulaby, F. and Long, D.G. (2015). Microwave Radar and Radiometric Remote Sensing. Artech House, Boston, MA.

      Vivone, G., Alparone, L., Chanussot, J., Dalla Mura, M., Garzelli, A., Licciardi, G., Restaino, R., Wald, L. (2015). A critical comparison among pansharpening algorithms. IEEE Transactions on Geoscience and Remote Sensing, 53(5), 2565–2586.

      Voisin, A. (2012). Classification supervisée d’images d’observation de la Terre à haute résolution par utilisation de méthodes markoviennes. Thesis, PhD Thesis, University of Nice Sophia Antipolis, France.

      Voisin, A., Krylov, V., Moser, G., Serpico, S., Zerubia, J. (2012). Multichannel hierarchical image classification using multivariate copulas. IS&T/SPIE Electronic Imaging, International Society for Optics and Photonics, Bellingham, WN.

      Voisin, A., Krylov, V., Moser, G., Serpico, S., Zerubia, J. (2014). Supervised classification of multi-sensor and multi-resolution remote sensing images with a hierarchical copula-based approach. IEEE Transactions on Geoscience and Remote Sensing, 52(6), 3346–3358.

      Wald, L. (1999). Some terms of reference in data fusion. IEEE Transactions on Geoscience and Remote Sensing, 37(3), 1190–1193.

      Waltz, E. and Llinas, J. (1990). Multisensor Data Fusion, vol. 685. Artech House, Boston, MA.

      Waske, B. and van der Linden, S. (2008). Classifying multilevel imagery from SAR and optical sensors by decision fusion. IEEE Transactions on Geoscience and Remote Sensing, 46(5), 1457–1466.

      Willsky, A. (2002). Multiresolution Markov models for signal and image processing. Proceedings of the IEEE, 90(8), 1396–1458.

      Yang, B., Li, S., Sun, F. (2007). Image fusion using nonsubsampled contourlet transform. IEEE International Conference on Image and Graphics, pp. 719–724.

      Zhang, Y. and Hong, G. (2005). An IHS and wavelet integrated approach to improve pan-sharpening visual quality of natural colour IKONOS and QuickBird images. Information Fusion, 6(3), 225–234.

      Zhang, G. and Kingsbury, N. (2015). Variational Bayesian image restoration with group-sparse modeling of wavelet coefficients. Digital Signal Processing: A Review Journal, 47, 157–168.

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