Santiago VELASCO-FORERO

Lectures Notes in Computer Science

  1. Inner-Cheeger Opening and Applications S. Velasco-Forero, Mathematical Morphology and Its Applications to Signal and Image Processing, LNCS, vol. 9082, pp. 75-85, 2015

  2. Supervised morphology for tensor structure-valued images based on symmetric divergence kernels S. Velasco-Forero and J. Angulo, in Geometric Science of Information, vol. 8085, pp. 543-550, 2013.

  3. On nonlocal mathematical morphology S. Velasco-Forero and J. Angulo, Mathematical Morphology and Its Applications to Signal and Image Processing, LNCS, vol. 7883, pp. 219-230, 2013.

  4. Mathematical morphology for real-valued images on Riemannian manifolds J. Angulo and S. Velasco-Forero, Mathematical Morphology and Its Applications to Signal and Image Processing, LNCS, vol.7883, pp. 279-291, 2013.

  5. Stochastic morphological filtering and Bellman-Maslov chains J. Angulo and S. Velasco-Forero, Mathematical Morphology and Its Applications to Signal and Image Processing, LNCS, vol. 7883, pp. 171-182, 2013.

  6. Mathematical morphology for vector images using statistical depth S. Velasco-Forero and J. Angulo, in Mathematical Morphology and Its Applications to Image and Signal Processing, LNCS, vol. 6671, pp. 355-366, 2011

  7. Sparse mathematical morphology using non-negative matrix factorization J. Angulo and S. Velasco-Forero, in Mathematical Morphology and Its Applications to Image and Signal Processing, LNCS, vol. 6671, pp. 1-12, 2011

  8. Hit-or-Miss Transform in Multivariate Images S.Velasco-Forero and J.Angulo in Advanced Concepts for Intelligent Vision Systems, vol. 6474, 2010, pp. 452-463, LNCS, 2010.

Conference Proceedings

  1. Retrieval of Human Subjects from Depth Sensor Data, A. Giachetti et al., Eurographics Workshop on 3D Object Retrieval, 2016.

  2. Selection of Stochastic Watershed Hierarchies, A. Fehri, S. Velasco-Forero and F. Meyer, EUSIPCO 2016.

  3. Objects co-segmentation: Propagated from simpler images M. Chen, S. Velasco-Forero, I. Tsang and T.J. Cham, IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp. 1682-1686, 2015

  4. Anomaly detection and important band selection for hyperspectral images via sparse PCA, S. Velasco-Forero, M. Chen, A. Goh and S.K. Pang, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014.

  5. A comparative analysis of covariance matrix estimation in anomaly detection, S. Velasco-Forero, M. Chen, A. Goh and S.K. Pang, 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014.

  6. Robust Anomaly Detection in Hyperspectral imaging J. Frontera-Pons et al., IEEE International Geoscience and Remote Sensing Symposium (IGARSS), pp. 4604-4607, 2014.

  7. SHREC-14 Track: Retrieval and classification on Textured 3D Models, S. Biasotti et al., accepted to Eurographics Workshop on 3D Object Retrieval, 2014.

  8. SHREC’13 Track: Retrieval on textured 3D models, A. Cerri et al., Eurographics Workshop on 3D Object Retrieval, pp. 73-80, 2013.

  9. Multivariate diffusion tensor and induced morphological segmentation, S. Velasco-Forero, M. Marin-Mc Gee and M. VĂ©lez-Reyes, 5th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2013

  10. Robust RX Anomaly Detector without covariance matrix estimation, S.Velasco-Forero and J. Angulo, 2012 4th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), June, pp. 1-4, 2012.

  11. Edge Extraction by statistical dependence analysis: Application to multi-angular Worldview-2 series, L. Gueguen, S. Velasco-Forero and P. Soille, IGARSS International Geoscience and Remote Sensing Symposium, pp. 3447-3450, 2012.

  12. Multiclass ordering for filtering and classification of hyperspectral images, S. Velasco-Forero and J. Angulo, 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1-4, 2011.

  13. Spatial structures detection in hyperspectral images using mathematical morphology, S.Velasco-Forero and J.Angulo, 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), pp. 1-4, 2010.

  14. Morphological processing of hyperspectral images using kriging-based supervised ordering, S.Velasco-Forero and J.Angulo in IEEE-International Conference on Image Processing (ICIP)- Hong Kong, 2010, pp. 1409-1412.

  15. Structurally adaptive mathematical morphology on nonlinear scale-space representations, J. Angulo and S.Velasco-Forero, in IEEE-International Conference on Image Processing (ICIP)- Hong Kong 2010, pp. 121-124.

  16. Semi-supervised hyperspectral image segmentation using regionalized stochastic watershed, J.Angulo and S.Velasco-Forero, in SPIE symposium on SPIE Defense, Security, and Sensing, April, Orlando, USA, 2010.

  17. Statistical shape modeling using morphological representations, S.Velasco-Forero and J.Angulo,in 20th International Conference on Pattern Recognition (ICPR), Istambul, Turkey, 2010, pp. 3537-3540.

  18. Parameters selection of morphological scale-space decomposition for hyperspectral images using tensor modeling, S.Velasco-Forero and J.Angulo, in SPIE symposium on SPIE Defense, Security, and Sensing, April, Orlando, USA, 2010.

  19. Morphological image distances for hyperspectral dimensionality exploration using kernel-PCA and Isomap, S.Velasco-Forero, J.Angulo, and J.Chanussot,, in IEEE - International Geoscience and Remote Sensing Symposium, July, Cape Town, South Africa, 2009.

  20. Multiscale stochastic watershed for unsupervised hyperspectral image segmentation , J.Angulo, S.Velasco-Forero, and J.Chanussot, in IEEE International Geoscience and Remote Sensing Symposium, July, Cape Town,South Africa, 2009.

  21. Accelerating hyperspectral manifold learning using graphical processing units , S.Velasco-Forero and V.Manian, in SPIE Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XV, April, Orlando, USA, 2009.

  22. Morphological scale-space for hyperspectral images and dimensionality exploration using tensor modeling, S.Velasco-Forero and J.Angulo,, IEEE - Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, August, Grenoble, France, 2009.

  23. Improving hyperspectral image classification based on graphs using spatial preprocessing, S.Velasco-Forero and V.Manian, in IEEE - International Geosciences and Remote Sensing Symposium, 7-11 July, Boston, USA, 2008