Sistema de Visión Subacuático Inalámbrico Usando un Algoritmo de Compresión Progresivo con Región de Interés
Enviado: 15-11-2017
|Aceptado: 15-11-2017
|Publicado: 05-12-2017
Descargas
Palabras clave:
Compresión de Imagen, Transmisión de Datos, Sistemas de Comunicación, Teleoperación
Agencias de apoyo:
MINECO
DPI2014-57746-C3 (proyecto MERBOTS)
Generalitat Valenciana
PROMETEO/2016/066
Universidad Jaume I
MASUMIA (P1-1B2015-68)
becas PREDOC/2012/47
PREDOC /2013/46
CNPq del Brasil
Resumen:
La creciente demanda en todo el mundo de sistemas de intervención submarina en diversos dominios de aplicación requiere sistemas más versátiles y económicos. Empleando un sistema de comunicación inalámbrica, los robots semiautónomos supervisados disponen de libertad de movimientos y, al mismo tiempo, permiten al operador obtener información visual y supervisar la intervención. Por otro lado, la velocidad de transmisión de datos típica de los canales inalámbricos submarinos es, en general, muy limitada, siendo necesaria la aplicación de técnicas de compresión avanzadas. En este artículo se presenta principalmente el algoritmo DEBT (Depth Embedded Block Tree) para la compresión progresiva de imágenes con región de interés (ROI). Los resultados demuestran ventajas con respecto a otros algoritmos de compresión, y la posibilidad de ejecución del algoritmo en tiempo real en ordenadores embebidos de bajo consumo basados en ARM.
Citas:
Adams, M., Kossentini, F., Sept 2000. Jasper: a software-based JPEG-2000 codec implementation. In: Image Processing, 2000. Proceedings. 2000 International Conference on. Vol. 2. pp. 53–56.
Calderbank, A., Daubechies, I., Sweldens, W., Yeo, B.-L., 1998. Wavelet transforms that map integers to integers. Applied and Computational Harmonic Analysis 5 (3), 332 – 369. URL: http://www.sciencedirect.com/science/article/pii/S1063520397902384 https://doi.org/10.1006/acha.1997.0238
Carreras, M., Ridao, P., García, R., Ribas, D., Palomeras, N., 2012. Inspección visual subacuática mediante robótica submarina. Revista Iberoamericana de Automática e Informática Industrial RIAI 9 (1), 34–45. https://doi.org/10.1016/j.riai.2011.11.011
Delaunay, X., Thiebaut, C., Chabert, M., Charvillat, V., Morin, G., Oct. 2010. Progressive coding of satellite images with regions of interest. In: On-Board Payload Data Compression Workshop. Toulouse, France.
Farr, N., Bowen, A., Ware, J., Pontbriand, C., Tivey, M., May 2010. An integrated, underwater optical /acoustic communications system. In: OCEANS 2010 IEEE - Sydney. pp. 1–6. https://doi.org/10.1109/OCEANSSYD.2010.5603510
Moinuddin, A., Khan, E., May 2006. Wavelet based embedded image coding using unified zero-block-zero-tree approach. In: Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on. Vol. 2. pp. II–II. https://doi.org/10.1109/ICASSP.2006.1660377
Pearlman, W., Islam, A., Nagaraj, N., Said, A., Nov 2004. Efficient, low-complexity image coding with a set-partitioning embedded block coder. Circuits and Systems for Video Technology, IEEE Transactions on 14 (11), 1219–1235. https://doi.org/10.1109/TCSVT.2004.835150
Pelekanakis, C., Stojanovic, M., Freitag, L., Sept 2003. High rate acoustic link for underwater video transmission. In: OCEANS 2003. Proceedings. Vol. 2. pp. 1091–1097 Vol.2. https://doi.org/10.1109/OCEANS.2003.178494
Prats, M., del Pobil, A. P., Sanz, P. J., 2013. Robot physical interaction through the combination of vision, tactile and force feedback. Applications to assistive robotics. Springer Tracts in Advanced Robotics, Volume 84. Springer Publishing Company, Incorporated. https://doi.org/10.1007/978-3-642-33241-8
Rehna, V. J., Kumar, M. K. J., 2012. Wavelet based image coding schemes: A recent survey. CoRR abs/1209.2515. URL: http://arxiv.org/abs/1209.2515
Ribas, J., Sura, D., Stojanovic, M., Sept 2010. Underwater wireless video transmission for supervisory control and inspection using acoustic OFDM. In: OCEANS 2010. pp. 1–9. https://doi.org/10.1109/OCEANS.2010.5663839
Said, A., Pearlman, W., Jun 1996. A new, fast, and efficient image codec based on set partitioning in hierarchical trees. Circuits and Systems for Video Technology, IEEE Transactions on 6 (3), 243–250. https://doi.org/10.1109/76.499834
Sanz, P. J., Pe-alver, A., Sales, J., Fornas, D., Fernández, J. J., Perez, J., Bernabé ´e, J. A., Oct 2013a. GRASPER: A multisensory based manipulation system for underwater operations. In: 2013 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, Manchester, UK. https://doi.org/10.1109/SMC.2013.689
Sanz, P. J., Pe-alver, A., Sales, J., Fernández, J. J., Pérez, J., Fornas, D., García, J., Marin, R., Sep 2015. Multipurpose underwater manipulation for archaeological intervention. In: Sixth International Workshop on Marine Technology (MARTECH'15). Cartagena, Spain.
Sanz, P. J., Prats, M., Ridao, P., Ribas, D., Oliver, G., Orti, A., September 2010. Recent progress in the RAUVI project. A reconfigurable autonomous underwater vehicle for intervention. In: 52-th International Symphosium ELMAR-2010. Zadar, Croatia, pp. 471–474.
Sanz, P. J., Ridao, P., Oliver, G., Casalino, G., Petillot, Y., Silvestre, C., Melchiorri, C., Turetta, A., Sept 2013b. TRIDENT: An european project targeted to increase the autonomy levels for underwater intervention missions. In: OCEANS'13 MTS/IEEE conference. San Diego, CA, pp. 1–10.
Shan Jiang, S. G., 2011. Electromagnetic wave propagation into fresh water. Journal of Electromagnetic Analysis and Applications 3 (7), 261–266. https://doi.org/10.4236/jemaa.2011.37042
Shaw, A., Al-Shamma'a, A., Wylie, S., Toal, D., Sept 2006. Experimental investigations of electromagnetic wave propagation in seawater. In: Microwave Conference, 2006. 36th European. pp. 572–575.
Siegel, M., King, R. W. P., Jul 1973. Electromagnetic propagation between antennas submerged in the ocean. Antennas and Propagation, IEEE Transactions on 21 (4), 507–513. https://doi.org/10.1109/TAP.1973.1140525
Stojanovic, M., Preisig, J., January 2009. Underwater acoustic communication channels: Propagation models and statistical characterization. Communications Magazine, IEEE 47 (1), 84–89. https://doi.org/10.1109/MCOM.2009.4752682
Subedar, M., Karam, L., Abousleman, G., May 2004. An embedded scalingbased arbitrary shape region-of-interest coding method for JPEG2000. In: Acoustics, Speech, and Signal Processing, 2004. Proceedings. (ICASSP '04). IEEE International Conference on. Vol. 3. pp. iii–681–4. https://doi.org/10.1109/ICASSP.2004.1326636
Taubman, D. S., Marcellin, M.W., 2001. JPEG 2000: Image Compression Fundamentals, Standards and Practice. Kluwer Academic Publishers, Norwell, MA, USA.
Usevitch, B., Mar 1996. Optimal bit allocation for biorthogonal wavelet coding. In: Data Compression Conference, 1996. DCC '96. Proceedings. pp. 387–395. https://doi.org/10.1109/DCC.1996.488344
W. B. Pennebaker and J. L. Mitchell, 1992. JPEG still image data compression standard. New York: Van Nostrand Reinhold, 1992.
Wheeler, F. W., Pearlman, W., 2000. Combined spatial and subband block coding of images. In: Image Processing, 2000. Proceedings. 2000 International Conference on. Vol. 3. pp. 861–864 vol.3. https://doi.org/10.1109/ICIP.2000.899592
Zhang, H., Meng, F., Aug 2012. Exploiting the skin effect using radio frequency communication in underwater communication. In: Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on. pp. 1150–1153. https://doi.org/10.1109/ICICEE.2012.305
