H. Aghighi, J. Trinder, Y. Tarabalka, and S. Lim, Dynamic Block-Based Parameter Estimation for MRF Classification of High-Resolution Images, IEEE Geoscience and Remote Sensing Letters, vol.11, issue.10, pp.1687-1691, 2014.
DOI : 10.1109/LGRS.2014.2305913

URL : https://hal.archives-ouvertes.fr/hal-01016505

A. Ambikapathi, T. Chan, C. Chi, and K. Keizer, Hyperspectral Data Geometry-Based Estimation of Number of Endmembers Using p-Norm-Based Pure Pixel Identification Algorithm, IEEE Transactions on Geoscience and Remote Sensing, vol.51, issue.5, pp.2753-2769, 2013.
DOI : 10.1109/TGRS.2012.2213261

P. M. Atkinson, Optimal ground-based sampling for remote sensing investigations: estimating the regional meant, International Journal of Remote Sensing, vol.49, issue.3, pp.559-567, 1991.
DOI : 10.1007/BF00897746

P. M. Atkinson, Mapping Sub-Pixel Boundaries from Remotely Sensed Images, Innovations in GIS, vol.4, pp.166-180, 1997.
DOI : 10.14358/pers.71.7.839

P. M. Atkinson, Issues of uncertainty in super-resolution mapping and their implications for the design of an inter-comparison study, International Journal of Remote Sensing, vol.32, issue.20, pp.5293-5308, 2009.
DOI : 10.1016/0034-4257(87)90015-0

P. M. Atkinson, E. Pardo-iguzquiza, and M. Chica-olmo, Downscaling Cokriging for Super-Resolution Mapping of Continua in Remotely Sensed Images, IEEE Transactions on Geoscience and Remote Sensing, vol.46, issue.2, pp.573-580, 2008.
DOI : 10.1109/TGRS.2007.909952

A. Boucher and P. C. Kyriakidis, Super-resolution land cover mapping with indicator geostatistics, Remote Sensing of Environment, vol.104, issue.3, pp.264-282, 2006.
DOI : 10.1016/j.rse.2006.04.020

C. A. Bouman and M. Shapiro, A multiscale random field model for Bayesian image segmentation, IEEE Transactions on Image Processing, vol.3, issue.2, pp.162-177, 1994.
DOI : 10.1109/83.277898

E. K. Burke, J. P. Newall, and R. F. Weare, A memetic algorithm for university exam timetabling, Lecture Notes in Computer Science, vol.1153, issue.15, pp.241-250, 1996.
DOI : 10.1007/3-540-61794-9_63

C. Chang and C. Lin, LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-27, 2011.
DOI : 10.1145/1961189.1961199

J. Cohen, A Coefficient of Agreement for Nominal Scales, Educational and Psychological Measurement, vol.20, issue.1, pp.37-46, 1960.
DOI : 10.1177/001316446002000104

R. Eglese, Simulated annealing: A tool for operational research, European Journal of Operational Research, vol.46, issue.3, pp.271-281, 1990.
DOI : 10.1016/0377-2217(90)90001-R

G. Fan and X. Xiang-gen, A Joint Multicontext and Multiscale Approach to Bayesian Image Segmentation, IEEE Transactions on Geoscience and Remote Sensing, vol.39, issue.12, pp.2680-2688, 2001.

G. M. Foody, Thematic Map Comparison, Photogrammetric Engineering & Remote Sensing, vol.70, issue.5, pp.627-633, 2004.
DOI : 10.14358/PERS.70.5.627

Y. H. Hu, H. B. Lee, and F. L. Scarpace, Optimal linear spectral unmixing, IEEE Transactions on Geoscience and Remote Sensing, vol.37, issue.1, pp.639-644, 1999.
DOI : 10.1109/36.739139

T. Kasetkasem, M. K. Arora, and P. K. Varshney, Super-resolution land cover mapping using a Markov random field based approach, Remote Sensing of Environment, vol.96, issue.3-4, pp.302-314, 2005.
DOI : 10.1016/j.rse.2005.02.006

X. Li, Y. Du, and F. Ling, Spatially adaptive smoothing parameter selection for Markov random field based sub-pixel mapping of remotely sensed images, International Journal of Remote Sensing, vol.75, issue.24, pp.7886-7901, 2012.
DOI : 10.1016/S0034-4257(01)00242-5

X. Li, Y. Du, and F. Ling, Super-Resolution Mapping of Forests with Bitemporal Different Spatial Resolution Images Based on the Spatial-Temporal Markov Random Field, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, issue.1, pp.29-39, 2014.

W. Liguo, W. Qunming, and L. Danfeng, Sub-Pixel Mapping Based on Sub-Pixel to Sub- Pixel Spatial Attraction Model, Geoscience and Remote Sensing Symposium (IGARSS), pp.593-596, 2011.

F. Ling, X. Li, Y. Du, and F. Xiao, Sub-pixel mapping of remotely sensed imagery with hybrid intra- and inter-pixel dependence, International Journal of Remote Sensing, vol.75, issue.1, pp.341-357, 2013.
DOI : 10.1016/S0034-4257(01)00242-5

P. Luciani and D. Chen, The impact of image and class structure upon sub-pixel mapping accuracy using the pixel-swapping algorithm, Annals of GIS, vol.10, issue.1, pp.31-42, 2011.
DOI : 10.1016/S0034-4257(01)00242-5

Y. Makido and A. Shortridge, Weighting Function Alternatives for a Subpixel Allocation Model, Photogrammetric Engineering & Remote Sensing, vol.73, issue.11, 2007.
DOI : 10.14358/PERS.73.11.1233

K. C. Mertens, B. De-baets, L. P. Verbeke, and R. R. De-wulf, Direct sub-pixel mapping exploiting spatial dependence, IEEE International IEEE International IEEE International Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004, pp.3046-3049, 2004.
DOI : 10.1109/IGARSS.2004.1370340

K. C. Mertens, B. De-baets, L. P. Verbeke, and R. R. De-wulf, A sub???pixel mapping algorithm based on sub???pixel/pixel spatial attraction models, International Journal of Remote Sensing, vol.68, issue.15, pp.3293-3310, 2006.
DOI : 10.1016/S0034-4257(01)00242-5

K. C. Mertens, L. P. Verbeke, E. I. Ducheyne, and R. R. De-wulf, Using genetic algorithms in sub-pixel mapping, International Journal of Remote Sensing, vol.79, issue.21, pp.4241-4247, 2003.
DOI : 10.1080/01431160310001595073

K. C. Mertens, L. P. Verbeke, T. Westra, and R. R. De-wulf, Sub-pixel mapping and sub-pixel sharpening using neural network predicted wavelet coefficients, Remote Sensing of Environment, vol.91, issue.2, pp.225-236, 2004.
DOI : 10.1016/j.rse.2004.03.003

E. Mohn, N. L. Hjort, and G. O. Storvik, A Simulation Study of Some Contextual Classification Methods For Remotely Sensed Data, IEEE Transactions on Geoscience and Remote Sensing, vol.25, issue.6, pp.796-804, 1987.
DOI : 10.1109/TGRS.1987.289751

C. Persello and L. Bruzzone, A Novel Protocol for Accuracy Assessment in Classification of Very High Resolution Images, IEEE Transactions on Geoscience and Remote Sensing, vol.48, issue.3, pp.1232-1244, 2009.
DOI : 10.1109/TGRS.2009.2029570

J. Plaza, A. Plaza, R. Pérez, and P. Martnez, Joint Linear\Nonlinear Spectral Unmixing of Hyperspectral Image Data Geoscience and Remote Sensing Symposium, pp.4037-4040, 2007.

R. L. Powell, D. A. Roberts, P. E. Dennison, and L. L. Hess, Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil, Remote Sensing of Environment, vol.106, issue.2, pp.253-267, 2007.
DOI : 10.1016/j.rse.2006.09.005

J. Richards and X. Jia, Remote Sensing Digital Image Analysis: An Introduction, 2006.

A. J. Tatem, H. G. Lewis, P. M. Atkinson, and M. S. Nixon, Multiple-class land-cover mapping at the sub-pixel scale using a Hopfield neural network, International Journal of Applied Earth Observation and Geoinformation, vol.3, issue.2, pp.184-190, 2001.
DOI : 10.1016/S0303-2434(01)85010-8

A. J. Tatem, H. G. Lewis, P. M. Atkinson, and M. S. Nixon, Super-resolution land cover pattern prediction using a Hopfield neural network, Remote Sensing of Environment, vol.79, issue.1, pp.1-14, 2002.
DOI : 10.1016/S0034-4257(01)00229-2

M. W. Thornton, P. M. Atkinson, and D. A. Holland, Sub???pixel mapping of rural land cover objects from fine spatial resolution satellite sensor imagery using super???resolution pixel???swapping, International Journal of Remote Sensing, vol.25, issue.3, pp.473-491, 2006.
DOI : 10.1016/S0034-4257(01)00242-5

V. A. Tolpekin and A. Stein, Quantification of the Effects of Land-Cover-Class Spectral Separability on the Accuracy of Markov-Random-Field-Based Superresolution Mapping, IEEE Transactions on Geoscience and Remote Sensing, vol.47, issue.9, pp.3283-3297, 2009.
DOI : 10.1109/TGRS.2009.2019126

J. Verhoeye and R. Wulf, Land cover mapping at sub-pixel scales using linear optimization techniques, Remote Sensing of Environment, vol.79, issue.1, pp.96-104, 2002.
DOI : 10.1016/S0034-4257(01)00242-5

A. Villa, J. Chanussot, J. A. Benediktsson, and C. Jutten, Spectral Unmixing for the Classification of Hyperspectral Images at a Finer Spatial Resolution, IEEE Journal of Selected Topics in Signal Processing, vol.5, issue.3, pp.521-533, 2010.
DOI : 10.1109/JSTSP.2010.2096798

URL : https://hal.archives-ouvertes.fr/hal-00578890

Q. Wang, W. Shi, and L. Wang, Indicator Cokriging-Based Subpixel Land Cover Mapping With Shifted Images, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.7, issue.1, pp.327-339, 2014.
DOI : 10.1109/JSTARS.2013.2262927

Q. Wang, L. Wang, and D. Liu, Integration of spatial attractions between and within pixels for sub-pixel mapping, Journal of Systems Engineering and Electronics, vol.23, issue.2, pp.293-303, 2012.
DOI : 10.1109/JSEE.2012.00037

Q. Wang, L. Wang, and D. Liu, Particle swarm optimization-based sub-pixel mapping for remote-sensing imagery, International Journal of Remote Sensing, vol.75, issue.20, pp.6480-6496, 2012.
DOI : 10.1016/j.neucom.2007.08.033

X. Xu, Y. Zhong, and L. Zhang, Sub-pixel Mapping with Multiple Shifted Remotely Sensed Images Based on Attraction Model, Lecture Notes in Computer Science, vol.7202, issue.62, pp.482-489, 2012.
DOI : 10.1007/978-3-642-31919-8_62

Y. Xu and H. Huang, A Spatio–Temporal Pixel-Swapping Algorithm for Subpixel Land Cover Mapping, IEEE Geoscience and Remote Sensing Letters, vol.11, issue.2, pp.474-478, 2014.
DOI : 10.1109/LGRS.2013.2268153

J. Yu and M. Ekström, Multispectral image classification using wavelets: a simulation study, Pattern Recognition, vol.36, issue.4, pp.889-89810, 2003.
DOI : 10.1016/S0031-3203(02)00125-5

B. Zhang, S. Li, X. Jia, L. Gao, and M. Peng, Adaptive Markov Random Field Approach for Classification of Hyperspectral Imagery, IEEE Geoscience and Remote Sensing Letters, vol.8, issue.5, pp.973-977, 2011.
DOI : 10.1109/LGRS.2011.2145353

L. Zhang, K. Wu, Y. Zhong, and P. Li, A new sub-pixel mapping algorithm based on a BP neural network with an observation model, Neurocomputing, vol.71, issue.10-12, pp.10-12, 2008.
DOI : 10.1016/j.neucom.2007.08.033

Y. Zhong and L. Zhang, Sub-pixel mapping based on artificial immune systems for remote sensing imagery, Pattern Recognition, vol.46, issue.11, pp.2902-2926, 2013.
DOI : 10.1016/j.patcog.2013.04.009