Aggregation of Descriptive Regularization and Fuzzy Logic Techniques for Enhanced Remote Sensing Imaging
A. Castillo Atoche, O. Palma Marrufo, R. Peon Escalante
2014
Abstract
In this paper, the aggregation of the descriptive regularization and Fuzzy-Logic techniques is proposed for the enhancement/reconstruction of the power spatial spectrum pattern (SSP) of the wave field scattered from remotely sensed scenes. In particular, the Weighted Constrain Least Square (WCLS) and the Fuzzy anisotropic diffusion techniques are algorithmically adapted and implemented in a parallel fashion using commodity graphic processor units (GPUs) improving the time performance of real-time remote sensing applications. Experimental results show the performance efficiency both in resolution enhancement and in computational complexity reduction metrics with the presented approach.
References
- Castillo Atoche, A., Shkvarko, Y., Torres Roman, D., and Perez Meana, H. (2009). Convex regularization-based hardware/software co-design for real-time enhancement of remote sensing imagery. Journal of Real-Time Image Processing, 4(3):261-272.
- Castillo Atoche, A., Torres Roman, D., and Shkvarko, Y. (2010). Experiment design regularization-based hardware/software codesign for real-time enhanced imaging in uncertain remote sensing environment. EURASIP Journal on Advances in Signal Processing, 2010:10.
- Chang, C.-I. (2007). Hyperspectral data exploitation: theory and applications. Wiley-Interscience.
- Goodman, J. A., Kaeli, D., and Schaa, D. (2011). Accelerating an imaging spectroscopy algorithm for submerged marine environments using graphics processing units. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 4(3):669-6762.
- Henderson, F. M. and Lewis, A. J. (1998). Principles and applications of imaging radar. Manual of remote sensing. John Wiley and sons, 3rd edition.
- Liu, F., S. F. J. and Plaza, A. (2011). Parallel hyperspectral image processing on distributed multicluster systems. Journal of Applied Remote Sensing, 5(1).
- Paz, A. and Plaza, A. (2010). Clusters versus gpus for parallel target and anomaly detection in hyperspectral images. EURASIP J. Adv. Signal Process, 2010:1-18.
- Sanders, J. and Kandrot, E. (2011). CUDA by Example:An Introduction to General-Purpose GPU Programming. Addison-Wesley Professional, 1st edition.
- Shkvarko, Y., Perez-Meana, and Castillo Atoche, A. (2008). Enhanced radar imaging in uncertain environment: a descriptive experiment design regularization paradigm. International Journal of Navigation and Observation, 8:11.
- Shkvarko, Y. V. (2010). Unifying experiment design and convex regularization techniques for enhanced imaging with uncertain remote sensing data; part i: Theory. Geoscience and Remote Sensing, IEEE Transactions on, 48(1):82-95.
- Song, J. and Tizhoosh, H. R. (2003). Fuzzy anisotropic diffusion: A rule based approach. World Multiconference on Systemics, Cyebernetics and Informatics, pages 241-246.
- Yu, J., Liu, A., Yang, Y., and Zhao, Y. (2013). Analysis of sea ice motion and deformation using amsr-e data from 2005 to 2007. International Journal of Remote Sensing, 34(12):4127-4141.
Paper Citation
in Harvard Style
Castillo Atoche A., Palma Marrufo O. and Peon Escalante R. (2014). Aggregation of Descriptive Regularization and Fuzzy Logic Techniques for Enhanced Remote Sensing Imaging . In Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014) ISBN 978-989-758-053-6, pages 193-198. DOI: 10.5220/0005154301930198
in Bibtex Style
@conference{fcta14,
author={A. Castillo Atoche and O. Palma Marrufo and R. Peon Escalante},
title={Aggregation of Descriptive Regularization and Fuzzy Logic Techniques for Enhanced Remote Sensing Imaging},
booktitle={Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)},
year={2014},
pages={193-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005154301930198},
isbn={978-989-758-053-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the International Conference on Fuzzy Computation Theory and Applications - Volume 1: FCTA, (IJCCI 2014)
TI - Aggregation of Descriptive Regularization and Fuzzy Logic Techniques for Enhanced Remote Sensing Imaging
SN - 978-989-758-053-6
AU - Castillo Atoche A.
AU - Palma Marrufo O.
AU - Peon Escalante R.
PY - 2014
SP - 193
EP - 198
DO - 10.5220/0005154301930198