974
Views
239
CrossRef citations to date
0
Altmetric
Original Articles

High-resolution satellite scene classification using a sparse coding based multiple feature combination

, , &
Pages 2395-2412 | Received 31 Jul 2010, Accepted 11 Feb 2011, Published online: 12 Oct 2011

References

  • Aharon , M. , Elad , M. and Bruckstein , A. 2006 . K-svd: an algorithm for designing overcomplete dictionaries for sparse representation . IEEE Transactions on Signal Processing , 54 : 4311 – 4322 .
  • Ahonen , T. , Matas , J. , He , C. and Pietikäinen , M. 2009 . Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features . Lecture Notes in Computer Science , 5575 : 61 – 70 .
  • Amarsaikhan , D. and Douglas , T. 2004 . Data fusion and multisource image classification . International Journal of Remote Sensing , 25 : 3529 – 3539 .
  • Barandela , R. and Juarez , M. 2002 . Supervised classification of remotely sensed data with ongoing learning capability . International Journal of Remote Sensing , 23 : 4965 – 4970 .
  • Bloch , I. , Milisavljevic , N. and Acheroy , M. 2007 . Multisensor data fusion for spaceborne and airborne reduction of mine suspected areas . International Journal of Advanced Robotic Systems , 4 : 173 – 186 .
  • Borghys , D. , Yvinec , Y. , Perneel , C. , Pizurica , A. and Philips , W. 2006 . Supervised feature-based classification of multi-channel SAR images . Pattern Recognition Letters , 27 : 252 – 258 . Special Issue on Pattern Recognition for Remote Sensing
  • Bruckstein , A. , Donoho , D. and Elad , M. 2009 . From sparse solutions of systems of equations to sparse modeling of signals and images . Society for Industrial and Applied Mathematics Review , 51 : 34 – 81 .
  • Candès , E. , Romberg , J. and Tao , T. 2006 . Stable signal recovery from incomplete and inaccurate measturements . Communications on Pure and Applied Mathematics , 59 : 1207 – 1223 .
  • Candès , E. and Tao , T. 2006 . Near-optimal signal recovery from random projections: Universal encoding strategies? . IEEE Transactions on Information Theory , 52 : 5406 – 5425 .
  • Chang, C.-C. and Lin, C.-J., 2001, LIBSVM: a library for support vector machines. Available online at (accessed 31 October 2010) http://www.csie.ntu.edu.tw/~cjlin/libsvm (http://www.csie.ntu.edu.tw/~cjlin/libsvm)
  • Cheng , B. , Yang , J. , Yan , S. and Huang , T. 2010 . Learning with l1 graph for image analysis . IEEE Transactions on Image Processing , 19 : 858 – 866 .
  • Dai, D.-X. and Yang, W., 2011, Satellite image classification via two-layer sparse coding with biased image representation. IEEE Geoscience and Remote Sensing Letters, 8, pp. 173–176. Available online at (accessed 31 October 2010) http://dsp.whu.edu.cn/cn/staff/yw/HRSscene.html (http://dsp.whu.edu.cn/cn/staff/yw/HRSscene.html)
  • Donoho , D. 2006 . For most large underdetermined systems of linear equation the minimal l 1-norm solution is also the sparsest solution . Communication on Pure and Applied Mathematics , 59 : 797 – 829 .
  • Foody , G.M. 1996 . Approaches for the production and evaluation of fuzzy land cover classification from remotely-sensed data . International Journal of Remote Sensing , 17 : 1317 – 1340 .
  • Franklin , S.E. , Peddle , D.R. , Dechka , J.A. and Stenhouse , G.B. 2002 . Evidential reasoning with Landsat TM, DEM and GIS data for land cover classification in support of grizzly bear habitat mapping . International Journal of Remote Sensing , 23 : 4633 – 4652 .
  • Gallego , F.J. 2004 . Remote sensing and land cover area estimation . International Journal of Remote Sensing , 25 : 3019 – 3047 .
  • Gehler , P. and Nowozin , S. On Feature Combination for Multiclass Object Classification . Proceedings of the 12th IEEE International Conference on Computer Vision . October 29 September–2 2009 , Kyoto, Japan. pp. 221 – 228 . Washington, DC : IEEE Computer Society .
  • Lazebnik , S. , Schmid , C. and Ponce , J. Beyond bags of features: spatial pyramid matching for recognizing natural scene categories . Proceedings of the 2006 IEEE Conference on Computer Vision and Pattern Recognition . 22–17 June 2006 , New York, NY. Vol. 2 , pp. 2169 – 2178 . Washington, DC : IEEE Computer Society .
  • Lewicki , M.S. and Sejnowski , T.J. 2000 . Learning overcomplete representations . Neural Computation , 12 : 337 – 365 .
  • Li , C.-S. and Castelli , V. Deriving texture feature set for content-based retrieval of satellite image database . Proceedings of the 1997 International Conference on Image Processing . October 26–29 1997 , Santa Barbara, CA. Vol. 1 , pp. 576 – 579 . Washington, DC : IEEE Computer Society .
  • Lowe , D.G. 2004 . Distinctive image features from scale-invariant keypoints . International Journal of Computer Vision , 60 : 91 – 110 .
  • Lu , D. and Weng , Q. 2007 . A survey of image classification methods and techniques for improving classification performance . International Journal of Remote Sensing , 28 : 823 – 870 .
  • Marques , J.F. 2005 . Naming from definition: the role of feature type and feature distinctiveness . International Journal of Remote Sensing , 58 : 603 – 611 .
  • Mikolajczyk , K. and Schmid , C. 2005 . A performance evaluation of local descriptors . IEEE Transactions on Pattern Analysis and Machine Intelligence , 27 : 1615 – 1630 .
  • Munoz-Mari , J. , Camps-Valls , G. , Gomez-Chova , L. and Calpe-Maravilla , J. Combination of one-class remote sensing image classifiers . Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium . July 23–28 2007 , Barcelona, Spain. pp. 1509 – 1512 . Piscataway, NJ : IEEE Geoscience and Remote Sensing Society .
  • Ojala , T. , Pietikainen , M. and Maenpaa , T. 2002 . Multiresolution gray-scale and rotation invarianat texture classification with local binary patterns . IEEE Transactions on Pattern Analysis and Machine Intelligence , 24 : 971 – 987 .
  • Olshausen , B.A. Learing sparse, overcomplete representation of time-varying natural images . Proceedings of the 2003 IEEE International Conference on Image Processing . September 14–17 2003 , Barcelona, Spain. Vol. 1 , pp. 41 – 44 . Washington, DC : IEEE Computer Society .
  • Olshausen , B.A. and Field , D.J. 1996 . Emergence of simple-cell receptive field properties by learning a sparse code for natural images . Nature , 381 : 607 – 609 .
  • Olshausen , B.A. and Field , D.J. 1997 . Sparse coding with an overcomplete basis set: a strategy employed by V1? . Vision Research , 37 : 3311 – 3325 .
  • Ruiz , L.A. , Fdez-Sarra , A. and Recio , J.A. 2004 . Texture feature extraction for classification of remote sensing data using wavelet decomposition: a comparative study . International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences , 35 : 1109 – 1114 .
  • Salappa , A. , Doumpos , M. and Zopounidis , C. 2007 . Feature selection algorithms in classification problems: an experimental evaluation . International Journal of Remote Sensing , 22 : 199 – 212 .
  • Shimoni , M. , Borghys , D. , Heremans , R. , Perneel , C. and Acheroy , M. 2009 . Fusion of PolSAR and PolInSAR data for land cover classification . International Journal of Applied Earth Observation and Geoinformation , 11 : 169 – 180 .
  • Tan , X. and Triggs , B. 2010 . Enhanced local texture feature sets for face recognition under difficult lighting conditions . IEEE Transactions on Image Processing , 19 : 1635 – 1650 .
  • Wright , J. , Yang , A.Y. , Ganesh , A. , Sastry , S.S. and Ma , Y. 2009 . Robust face recognition via sparse representation . IEEE Transactions on Pattern Analysis and Machine Intelligence , 31 : 210 – 227 .
  • Xia , G.-S. , Yang , W. , Delon , J. , Gousseau , Y. , Sun , H. and Maitre , H. Structural high-resolution satellite image indexing . Proceedings of 2010 ISPRS, TC VII Symposium (Part A): 100 Years ISPRS–Advancing Remote Sensing Science . July 5–7 2010 , Vienna, Austria. pp. 298 – 303 . Vienna : Vienna University of Technology .
  • Yang , J. , Wright , J. , Huang , T. and Ma , Y. Image super-resolution as sparse representation of raw image patches . Proceedings of the 2008 IEEE Conference on Computer Vision and Pattern Recognition . June 23–28 2008 , Anchorage, AK. pp. 1 – 8 . Washington, DC : IEEE Computer Society .
  • Yang , J. , Yu , K. , Gong , Y. and Huang , T. Linear spatial pyramid matching using sparse coding for image classification . Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition . June 20–25 2009 , Miami, FL. pp. 1794 – 1801 . Washington, DC : IEEE Computer Society .
  • Yin , Q. and Guo , P. Multispectral remote sensing image classification with multiple features . Proceedings of the Sixth International Conference on Machine Learning and Cybernetics . August 19–22 2007 , Hong Kong. Vol. 1 , pp. 360 – 365 . New York, , NY : IEEE Systems, Man, and Cybernetics Society .
  • Yu , K. , Zhang , T. and Gong , Y. 2009 . Nonlinear learning using local coordinate coding . Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems . December 7–12 2009 , Vancouver BC, Canada. Cambridge, MA : The MIT Press .
  • Zou , T. , Yang , W. , Dai , D. and Sun , H. 2010 . Polarimetric SAR image classification using multi-features combination and extremely randomized clustering forests . EURASIP Journal on Advances in Signal Processing , 2010 : 465612 doi: doi:10.1155/2010/4656122

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.