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Hardware Technology and Programming Languages for Reconfigurable Devices

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Wireless Multimedia Sensor Networks on Reconfigurable Hardware
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Abstract

This chapter discusses the hardware technology and programming languages for reconfigurable devices. The first part of the chapter discusses the technology available and the advantages of field programmable gate arrays (FPGAs) for implementation in hardware constrained environments such as wireless multimedia sensor networks and describes the range of FPGA technology and internal architectures using examples from Xilinx and Altera FPGA families. The second part of the chapter presents an overview of hardware description languages for reconfigurable devices. Here, ranges of available languages from lower-level languages like VHDL and Verilog to higher-level C-based languages are discussed. The chapter also contains an introduction to the Handel-C programming language which will be used in the next chapter for the processor specification. The DK Design Suite methodology used by Celoxica is also discussed.

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References

  1. Achanta, R., Estrada, F., Wils, P., Süsstrunk, S.: Salient region detection and segmentation. In: Proceedings of the 6th International Conference on Computer Vision Systems (ICVS’08), pp. 66–75. Springer, Berlin (2008). URL http://dl.acm.org/citation.cfm?id=1788524.1788532

  2. Achanta, R., Hemami, S., Estrada, F., Susstrunk, S.: Frequency-tuned salient region detection. In: IEEE Conference on Computer Vision and Pattern Recognition, 2009 (CVPR 2009), pp. 1597–1604 (2009). doi:10.1109/CVPR.2009.5206596

    Google Scholar 

  3. Acharya, T., Tsai, P.S.: JPEG2000 Standard for Image Compression: Concepts, Algorithms and VLSI Architectures. Wiley-Interscience, Hoboken (2004)

    Book  Google Scholar 

  4. Aghajan, H., Cavallaro, A.: Multi-Camera Networks: Principles and Applications. Academic, London (2009)

    Google Scholar 

  5. Akyildiz, I.F., Melodia, T., Chowdhury, K.R.: A survey on wireless multimedia sensor networks. Comput. Netw. 51(4), 921–960 (2007). doi:10.1016/j.comnet.2006.10.002. URL http://dx.doi.org/10.1016/j.comnet.2006.10.002

  6. Almalkawi, I., Zapata, M., Al-Karaki, J., Morillo-Pozo, J.: Wireless multimedia sensor networks: Current trends and future directions. Sensors (Basel) 10(7), 6662–6717 (2010)

    Google Scholar 

  7. Altera: Altera Stratix-V. http://www.altera.com/devices/fpga/stratix-fpgas/stratix-v/stxv-index.jsp (2013)

  8. Altera: Nios II Processor. http://www.altera.com.my/devices/processor/nios2/ni2-index.html (2011)

  9. Altera: Stratix II datasheet. http://www.altera.com.my/literature/hb/stx2/stx2_sii51002.pdf (2007)

  10. Ammari, A., Jemai, A.: Multiprocessor platform-based design for multimedia. IET Comput. Digit. Tech. 3(1), 52 –61 (2009). doi:10.1049/iet-cdt:20070168

    Article  Google Scholar 

  11. Angelopoulou, M.E., Masselos, K., Cheung, P.Y., Andreopoulos, Y.: Implementation and comparison of the 5/3 lifting 2d discrete wavelet transform computation schedules on fpgas. J. Signal Process. Syst. 51(1), 3–21 (2008). doi:10.1007/ s11265-007-0139-5. URL http://dx.doi.org/10.1007/s11265-007-0139-5

    Google Scholar 

  12. ARM Ltd.: ARM architectures. http://www.arm.com/products/processors/index.php (2011)

  13. Arnold, M.G.: Verilog Digital Computer Design: Algorithms into Hardware. Prentice Hall, Upper Saddle River (1999)

    Google Scholar 

  14. Bhattar, R.K., Ramakrishnan, K., Dasgupta, K.: Strip based coding for large images using wavelets. Signal Process. Image Commun. 17(6), 441–456 (2002). doi:10. 1016/S0923-5965(02)00019-X. URL  http://www.sciencedirect.com/science/article/pii/S092359650200019Xhttp://www.sciencedirect.com/science/article/pii/S092359650200019X

  15. Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. Int. J. Comput. Vis. 74(1), 59–73 (2007). doi:10.1007/s11263-006-0002-3. URL http://dx.doi.org/10.1007/s11263-006-0002-3

    Google Scholar 

  16. Bruce, N.D.B., Tsotsos, J.K.: Saliency, attention, and visual search: An information theoretic approach. J. Vis. 9(3), 1–24 (2009)

    Article  Google Scholar 

  17. Burt, P.J., Adelson, E.H.: A multiresolution spline with application to image mosaics. ACM Trans. Graph. 2(4), 217–236 (1983). doi:10.1145/245.247. URL http://doi.acm.org/10.1145/245.247

  18. Cadambi, S., Weener, J., Goldstein, S.C., Schmit, H., Thomas, D.E.: Managing pipeline-reconfigurable fpgas. In: Proceedings of the 1998 ACM/SIGDA Sixth International Symposium on Field Programmable Gate Arrays (FPGA ’98), pp. 55–64. ACM, New York (1998). doi:10.1145/275107. 275120. URL http://doi.acm.org/10.1145/275107.275120

  19. Cardoso, J.F.: High-order contrasts for independent component analysis. Neural Comput. 11, 157–192 (1999). doi:http: //dx.doi.org/10.1162/089976699300016863. URL http://dx.doi.org/10.1162/089976699300016863

    Google Scholar 

  20. Cassereau, P.M.: Wavelet-based image coding. In: Watson, A.B. (ed.) Digital Images and Human Vision, pp. 12–21. The MIT Press, Cambridge (1993)

    Google Scholar 

  21. Celoxica: Celoxica RC10. www.europractice.rl.ac.uk/vendors/agility_rc10.pdf (2005)

  22. Celoxica: Celoxica RC230E. http://babbage.cs.qc.edu/courses/cs345/Manuals/RC200_203%20Manual.pdf (2005)

  23. Celoxica: DK Design Suite. http://www.europractice.stfc.ac.uk/vendors/agility_dk4.pdf (2005)

  24. Celoxica: DK4 Handel-C Language Reference Manual. http://babbage.cs.qc.edu/courses/cs345/Manuals/HandelC.pdf (2005)

  25. Charfi, Y., Wakamiya, N., Murata, M.: Network-adaptive image and video transmission in camera-based wireless sensor networks. In: IEEE International Conference on Distributed Smart Cameras, pp. 336–343 (2007). URL http://dblp.uni-trier.de/db/conf/icdsc/icdsc2007.html#CharfiWM07

  26. Cheung, S.C.S., Kamath, C.: Robust background subtraction with foreground validation for urban traffic video. EURASIP J. Appl. Signal Process. 14, 2330–2340 (2005). doi:10.1155/ASP.2005.2330. URL http://dx.doi.org/10.1155/ASP.2005.2330

  27. Chew, L.W., Ang, L.M., Seng, K.P.: New virtual spiht tree structures for very low memory strip-based image compression. IEEE Signal Process. Lett. 15, 389 –392 (2008). doi:10.1109/LSP.2008.920515

    Article  Google Scholar 

  28. Chew, L.W., Chia, W.C., Ang, L.M., Seng, K.P.: Very low-memory wavelet compression architecture using strip-based processing for implementation in wireless sensor networks. EURASIP J. Embed. Syst. 2009, 9:1–9:1 (2009). doi:10.1155/ 2009/479281. URL http://dx.doi.org/10.1155/2009/479281

  29. Chew, L.W., Chia, W.C., Ang, L.M., Seng, K.P.: Low-memory video compression architecture using strip-based processing for implementation in wireless multimedia sensor networks. Int. J. Sens. Netw. 11(1), 33–47 (2012). doi:10.1504/IJSNET. 2012.045033. URL http://dx.doi.org/10.1504/IJSNET.2012.045033

  30. Chia, W.C., Chew, L.W., Ang, L.M., Seng, K.P.: Low memory image stitching and compression for wmsn using strip-based processing. IJSNet 11(1), 22–32 (2012). URL http://dblp.uni-trier.de/db/journals/ijsnet/ijsnet11.html#ChiaCAS12

  31. Choi, S., Scrofano, R., Prasanna, V.K., Jang, J.W.: Energy-efficient signal processing using FPGAs. In: Proceedings of the 2003 ACM/SIGDA Eleventh International Symposium on Field Programmable Gate Arrays (FPGA ’03), pp. 225–234. ACM, New York (2003). doi:10.1145/ 611817.611850. URL http://doi.acm.org/10.1145/611817.611850

  32. Chrysafis, C., Ortega, A.: Line-based, reduced memory, wavelet image compression. IEEE Trans. Image Process. 9(3), 378–389 (2000). doi:10.1109/83.826776

    Article  MathSciNet  MATH  Google Scholar 

  33. Compton, K., Hauck, S.: Reconfigurable computing: A survey of systems and software. ACM Comput. Surv. 34(2), 171–210 (2002). doi:10.1145/508352.508353. URL http://doi.acm.org/10.1145/508352.508353

  34. Crossbow Technology: XBow SPB400–Stargate Gateway Datasheet. http://bullseye.xbow.com:81/Products/Product_pdf_files/Wireless_pdf/Stargate_Datasheet.pdf (2006)

  35. Crossbow Technology: XBow TELOSB Datasheet. http://bullseye.xbow.com:81/Products/Product_pdf_files/Wireless_pdf/TelosB_Datasheet.pdf (2007)

  36. Cucchiara, R.: Multimedia surveillance systems. In: Proceedings of the Third ACM International Workshop on Video Surveillance & Sensor Networks (VSSN ’05), pp. 3–10. ACM, New York (2005). doi:10.1145/1099396.1099399. URL http://doi.acm.org/10.1145/1099396.1099399

  37. Czarlinska, A., Kundur, D.: Reliable event-detection in wireless visual sensor networks through scalar collaboration and game-theoretic consideration. IEEE Trans. Multimed. 10(5), 675–690 (2008). doi:10.1109/TMM.2008.922775

    Article  Google Scholar 

  38. Daubechies, I., Sweldens, W.: Factoring wavelet transforms into lifting steps. J. Fourier Anal. Appl. 4(3), 247–269 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  39. Elazary, L., Itti, L.: A bayesian model for efficient visual search and recognition. Vis. Res. 50(14), 1338–1352 (2010)

    Article  Google Scholar 

  40. Estrin, G.: Organization of computer systems: The fixed plus variable structure computer. In: Papers Presented at the May 3–5, 1960, Western Joint IRE-AIEE-ACM Computer Conference (IRE-AIEE-ACM ’60) (Western), pp. 33–40. ACM, New York (1960). doi:10.1145/1460361.1460365. URL http://doi.acm.org/10.1145/1460361.1460365

  41. Faraji, I., Didehban, M., Zarandi, H.: Analysis of transient faults on a mips-based dual-core processor. In: International Conference on Availability, Reliability, and Security, 2010 (ARES ’10), pp. 125–130 (2010). doi:10.1109/ARES.2010.30

    Google Scholar 

  42. Fischler, M.A., Bolles, R.C.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981). doi:10. 1145/358669.358692. URL http://doi.acm.org/10.1145/358669.358692

  43. Foulsham, T., Underwood, G.: What can saliency models predict about eye movements? spatial and sequential aspects of fixations during encoding and recognition. J. Vis. 8(2) (2008). doi:10.1167/8.2. 6. URL http://www.journalofvision.org/content/8/2/6.abstract

  44. Frintrop, S.: Computational visual attention. In: Computer Analysis of Human Behavior, pp. 69–101. Springer, London (2011)

    Google Scholar 

  45. Frintrop, S., Jensfelt, P.: Attentional landmarks and active gaze control for visual slam. IEEE Trans. Robot. 24(5), 1054–1065 (2008). doi:10.1109/TRO.2008.2004977

    Article  Google Scholar 

  46. Fry, T., Hauck, S.: SPIHT image compression on FPGAs. IEEE Trans. Circuits Syst. Video Technol. 15(9), 1138–1147 (2005). doi:10.1109/TCSVT.2005.852625

    Article  Google Scholar 

  47. Garcia, V.: Keypoints Extraction. http://www.mathworks.com/matlabcentral/fileexchange/17894-keypoint-extraction (2007)

  48. Gautham, P., Parthasarathy, R., Balasubramanian, K.: Low-power pipelined mips processor design. In: Proceedings of the 2009 12th International Symposium on Integrated Circuits (ISIC ’09), pp. 462–465 (2009)

    Google Scholar 

  49. Girod, B., Aaron, A., Rane, S., Rebollo-Monedero, D.: Distributed video coding. Proc. IEEE 93(1), 71 –83 (2005). doi:10.1109/JPROC.2004.839619

    Article  Google Scholar 

  50. Gray, A., Lee, C., Arabshahi, P., Srinivasan, J.: Object-oriented reconfigurable processing for wireless networks. In: IEEE International Conference on Communications, 2002 (ICC 2002), vol. 1, pp. 497–501 (2002). doi:10.1109/ICC.2002.996903

    Google Scholar 

  51. Guo, C., Zhang, L.: A novel multiresolution spatiotemporal saliency detection model and its applications in image and video compression. IEEE Trans. Image Process. 19(1), 185–198 (2010). doi:10.1109/TIP.2009.2030969

    Article  MathSciNet  Google Scholar 

  52. Guo, W., Xu, C., Ma, S., Xu, M.: Visual attention based small object segmentation in natual images. In: 2010 17th IEEE International Conference on Image Processing (ICIP), pp. 1565–1568 (2010). doi:10.1109/ICIP.2010.5649841

    Google Scholar 

  53. Guo, X., Lu, Y., Wu, F., Zhao, D., Gao, W.: Wyner–ziv-based multiview video coding. IEEE Trans. Circuits Syst. Video Technol. 18(6), 713–724 (2008). doi:10.1109/TCSVT.2008.920970. URL http://dx.doi.org/10.1109/TCSVT.2008.920970

    Google Scholar 

  54. Gürses, E., Akan, Ö.: Multimedia communication in wireless sensor networks. Ann. Telecommun. 60(7), 872–900 (2005)

    Google Scholar 

  55. Haering, N., da Vitoria Lobo, N.: Visual Event Detection. The International Series in Video Computing. Springer, New York (2001). URL http://www.springer.com/computer/image+processing/book/978-0-7923-7436-7

  56. Harris, C., Stephens, M.: A combined corner and edge detector. In: Proceedings of Fourth Alvey Vision Conference, pp. 147–151 (1988)

    Google Scholar 

  57. HART Communication Protocol and Foundation: WirelessHART Overview. http://www.hartcomm.org/protocol/wihart/wireless_overview.html (2010)

  58. Hasan, M., Rahman, M., Hasan, M., Hasan, M., Ali, M.: An improved pipelined processor architecture eliminating branch and jump penalty. In: 2010 Second International Conference on Computer Engineering and Applications (ICCEA), vol. 1, pp. 621–625 (2010). doi:10.1109/ICCEA.2010.126

    Google Scholar 

  59. Hauser, J., Wawrzynek, J.: Garp: A mips processor with a reconfigurable coprocessor. In: Proceedings of the 5th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, 1997, pp. 12–21 (1997). doi:10.1109/FPGA.1997.624600

    Google Scholar 

  60. Hill, J., Szewczyk, R., Woo, A., Hollar, S., Culler, D., Pister, K.: System architecture directions for networked sensors. SIGPLAN Not. 35(11), 93–104 (2000). doi:10.1145/356989.356998. URL http://doi.acm.org/10.1145/356989.356998

  61. Ho-Phuoc, T., Guyader, N., Gurin-Dugu, A.: A functional and statistical bottom-up saliency model to reveal the relative contributions of low-level visual guiding factors. Cogn. Comput. 2, 344–359 (2010). doi:10.1007/s12559-010-9078-8. URL http://dx.doi.org/10.1007/s12559-010-9078-8

  62. Hu, F., Kumar, S.: QoS considerations in wireless sensor networks for telemedicine. In: Proceedings of SPIE ITCOM Conference, Orlando, FL (2003)

    Google Scholar 

  63. Hunter, R.D.M., Johnson, T.T.: Introduction to VHDL. Springer, Berlin (1995). http://www.springer.com/engineering/circuits+%26+systems/book/978-0-412-73130-3

  64. International, D.: XBee ZNet 2.5 Module. http://www.digi.com/support/productdetail?pid=3261 (2012). Accessed Nov 2012

  65. International, D.: XBee/XBee-Pro RF Module Datasheet. http://www.digi.com/pdf/ds_xbeezbmodules.pdf (2011). Accessed Nov 2012

  66. Itti, L., Koch, C.: A saliency-based search mechanism for overt and covert shifts of visual attention. Vis. Res. 40, 1489–1506 (2000)

    Article  Google Scholar 

  67. Itti, L., Koch, C., Niebur, E.: A model of saliency-based visual attention for rapid scene analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(11), 1254–1259 (1998). doi:10.1109/34.730558

    Article  Google Scholar 

  68. Itti, L., Rees, G., Tsotsos, J.: Models of bottom-up attention and saliency. In: Neurobiology of Attention, pp. 576–582. Elsevier, San Diego (2005)

    Google Scholar 

  69. James, W.: The Principles of Psychology. American Science Series: Advanced Course, vol. 1. H. Holt, New York (1918). URL http://books.google.com.my/books?id=lbtE-xb5U-oC

  70. Kahn, J.M., Katz, R.H., Pister, K.S.J.: Next century challenges: Mobile networking for Smart Dust. In: Proceedings of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking (MobiCom ’99), pp. 271–278. ACM, New York (1999). doi:10.1145/ 313451.313558. URL http://doi.acm.org/10.1145/313451.313558

  71. Koch, C., Ullman, S.: Shifts in selective visual attention: Towards the underlying neural circuitry. Hum. Neurobiol. 4(4), 219–27 (1985)

    Google Scholar 

  72. Kunt, M., Ikonomopoulos, A., Kocher, M.: Second-generation image-coding techniques. Proc. IEEE 73(4), 549–574 (1985). doi:10.1109/PROC.1985.13184

    Article  Google Scholar 

  73. Kwok, T.T.O., Kwok, Y.K.: Computation and energy efficient image processing in wireless sensor networks based on reconfigurable computing. In: Proceedings of the 2006 International Conference Workshops on Parallel Processing (ICPPW ’06), pp. 43–50. IEEE Computer Society, Washington, DC (2006). doi:10.1109/ ICPPW.2006.30. URL http://dx.doi.org/10.1109/ICPPW.2006.30

  74. Lee, S.H., Shin, J.K., Lee, M.: Non-uniform image compression using biologically motivated saliency map model. In: Proceedings of the 2004 Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004, pp. 525–530 (2004) doi:10.1109/ISSNIP.2004.1417516

    Google Scholar 

  75. Li, L.J., Su, H., Xing, E.P., Fei-Fei, L.: Object bank: A high-level image representation for scene classification and semantic feature sparsification. In: Advances in Neural Information Processing Systems. MIT Press, Cambridge (2010)

    Google Scholar 

  76. Li, X., Li, T.: Ecomips: An economic MIPS CPU design on FPGA. In: Proceedings of the 4th IEEE International Workshop on System-on-Chip for Real-Time Applications, 2004, pp. 291–294 (2004). doi:10.1109/IWSOC.2004.1319896

    Google Scholar 

  77. Liang, J., DeMenthon, D., Doermann, D.: Note: Mosaicing of camera-captured document images. Comput. Vis. Image Underst. 113(4), 572–579 (2009). doi:10. 1016/j.cviu.2008.12.004. URL http://dx.doi.org/10.1016/j.cviu.2008.12.004

  78. Libelium Comunicaciones Distribuidas S.L.: Libelium Waspmote technical guide. http://www.libelium.com/downloads/documentation/waspmote_technical_guide.pdf (2013)

  79. Lindeberg, T.: Feature detection with automatic scale selection. Int. J. Comput. Vis. 30(2), 79–116 (1998). doi:10.1023/ A:1008045108935. URL http://dx.doi.org/10.1023/A:1008045108935

    Google Scholar 

  80. Liu, L., Yuan, F.G., Zhang, F.: Development of wireless smart sensor for structural health monitoring. In: Proceedings of the 2005 Smart Structures and Materials - Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, vol. 5765, No. 20, pp. 176–186 (2005). doi:10.1117/ 12.600206. URL http://dx.doi.org/10.1117/12.600206

  81. Liu, T., Yuan, Z., Sun, J., Wang, J., Zheng, N., Tang, X., Shum, H.Y.: Learning to detect a salient object. IEEE Trans. Pattern Anal. Mach. Intell. 33(2), 353 –367 (2011). doi:10.1109/TPAMI.2010.70

    Article  Google Scholar 

  82. Liu, Y., Xie, G., Chen, P., Chen, J., Li, Z.: Designing an asynchronous FPGA processor for low-power sensor networks. In: International Symposium on Signals, Circuits and Systems, 2009 (ISSCS 2009), pp. 1–6 (2009). doi:10.1109/ISSCS.2009.5206091

    Google Scholar 

  83. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004). doi:10.1023/B:VISI.0000029664.99615.94. URL http://dx.doi.org/10.1023/B:VISI.0000029664.99615.94

    Google Scholar 

  84. Lukai Cai, S.V., Gajski, D.D.: Technical report cecs-03-11. Technical Report, Center for Embedded Computer Systems, University of California, Irvine, California, 2003

    Google Scholar 

  85. Magli, E., Mancin, M., Merello, L.: Low-complexity video compression for wireless sensor networks. In: Proceedings of the 2003 International Conference on Multimedia and Expo - Vol. 3 (ICME ’03), pp. 585–588. IEEE Computer Society, Washington, DC (2003). URL http://dl.acm.org/citation.cfm?id=1170746.1171773

  86. Mangharam, R., Rowe, A., Rajkumar, R.: FireFly: A cross-layer platform for real-time embedded wireless networks. R. Time Syst. 37(3), 183–231 (2007). doi:10.1007/s11241-007-9028-z. URL http://dx.doi.org/10.1007/s11241-007-9028-z

  87. Martin, D., Fowlkes, C., Tal, D., Malik, J.: The berkeley segmentation dataset. http://www.eecs.berkeley.edu/Research/Projects/CS/vision/bsds/ (2007)

  88. Medeiros, H., Park, J., Kak, A.: Distributed object tracking using a cluster-based kalman filter in wireless camera networks. IEEE J. Sel. Top. Signal Process. 2(4), 448–463 (2008). doi:10.1109/JSTSP.2008.2001310

    Article  Google Scholar 

  89. Mendi, E., Milanova, M.: Image segmentation with active contours based on selective visual attention. In: Proceedings of the 3rd WSEAS International Symposium on Wavelets Theory and Applications in Applied Mathematics, Signal Processing & Modern Science (WAV’09), pp. 79–84. World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, Wisconsin, USA (2009). URL http://dl.acm.org/citation.cfm?id=1561963.1561976

  90. (MERL), M.E.R.L.: Stereoscopic Video Sequences. ftp://ftp.merl.com/pub/avetro/mvc-testseq/orig-yuv/exit/ (2005)

  91. Merrill, W., Sohrabi, K., Girod, L., Elson, J., Newberg, F.: Open standard development platforms for distributed sensor networks. In: SPIE Unattended Ground Sensor Technologies and Applications IV, pp. 327–337 (2002)

    Google Scholar 

  92. Mikolajczyk, K., Schmid, C.: Scale and affine invariant interest point detectors. Int. J. Comput. Vis. 60(1), 63–86 (2004). doi:10.1023/B:VISI.0000027790.02288.f2. URL http://dx.doi.org/10.1023/B:VISI.0000027790.02288.f2

    Google Scholar 

  93. Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005). doi:10.1109/TPAMI. 2005.188. URL http://dx.doi.org/10.1109/TPAMI.2005.188

    Google Scholar 

  94. Mills, A., Dudek, G.: Image stitching with dynamic elements. Image Vis. Comput. 27(10), 1593–1602 (2009). doi:10. 1016/j.imavis.2009.03.004. URL http://dx.doi.org/10.1016/j.imavis.2009.03.004

  95. MIPS Technologies: MIPS architectures. http://www.mips.com/products/architectures/mips32/ (2008)

  96. Mulligan, G.: The 6lowpan architecture. In: Proceedings of the 4th Workshop on Embedded Networked Sensors (EmNets ’07), pp. 78–82. ACM, New York (2007). doi:10.1145/1278972.1278992. URL http://doi.acm.org/10.1145/1278972.1278992

  97. Ngau, C., Ang, L.M., Seng, K.: Low memory visual saliency architecture for data reduction in wireless sensor networks. IET Wirel. Sens. Syst. 2(2), 115 –127 (2012). doi:10.1049/iet-wss.2011.0038

    Article  Google Scholar 

  98. Omnivision: Omnivision OV16820. http://www.ovt.com/products/sensor.php?id=116 (2012)

  99. Ouerhani, N., Bracamonte, J., Hugli, H., Ansorge, M., Pellandini, F.: Adaptive color image compression based on visual attention. In: Proceedings of the 11th International Conference on Image Analysis and Processing, 2001, pp. 416–421 (2001). doi:10.1109/ICIAP.2001.957045

    Google Scholar 

  100. Patterson, D.A., Hennessy, J.L.: Computer Organization and Design: The Hardware/Software Interface, 3rd edn. Morgan Kaufmann Publishers Inc., San Francisco (2007)

    Google Scholar 

  101. Pearlman, W.A., Islam, A., Nagaraj, N., Said, A.: Efficient, low-complexity image coding with a set-partitioning embedded block coder. IEEE Trans. Circuits Syst. Video Technol. 14(11), 1219–1235 (2004). doi:10.1109/TCSVT. 2004.835150. URL http://dx.doi.org/10.1109/TCSVT.2004.835150

    Google Scholar 

  102. Pham, D.M., Aziz, S.: FPGA-based image processor architecture for wireless multimedia sensor network. In: 2011 IFIP 9th International Conference on Embedded and Ubiquitous Computing (EUC), pp. 100–105 (2011). doi:10.1109/EUC.2011.38

    Google Scholar 

  103. Pradhan, S.S., Ramchandran, K.: Distributed source coding using syndromes (discus): Design and construction. IEEE Trans. Inf. Theory 49(3), 626–643 (2006). doi:10.1109/TIT.2002.808103. URL http://dx.doi.org/10.1109/TIT.2002.808103

  104. Puri, R., Ramchandran, K.: Prism: An uplink-friendly multimedia coding paradigm. In: Proceedings of the 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003 (ICASSP ’03), vol. 4, pp. IV–856–859 (2003). doi:10.1109/ICASSP.2003.1202778

    Google Scholar 

  105. Quattoni, A., Torralba, A.: Indoor scene recognition database. http://web.mit.edu/torralba/www/indoor.html (2009)

  106. Rajagopalan, R., Varshney, P.: Data-aggregation techniques in sensor networks: a survey. IEEE Commun. Surv. Tutor. 8(4), 48 –63 (2006). doi:10.1109/COMST.2006.283821

    Article  Google Scholar 

  107. Ramdas, T., Ang, L.M., Egan, G.: Fpga implementation of an integer mips processor in handel-c and its application to human face detection. In: TENCON 2004. 2004 IEEE Region 10 Conference Volume A, vol. 1, pp. 36–39 (2004). doi:10.1109/TENCON.2004.1414350

    Google Scholar 

  108. Rapantzikos, K., Avrithis, Y., Kollias, S.: Spatiotemporal saliency for event detection and representation in the 3d wavelet domain: Potential in human action recognition. In: Proceedings of the 6th ACM International Conference on Image and Video Retrieval (CIVR ’07), pp. 294–301. ACM, New York (2007). doi:10.1145/1282280.1282326. URL http://doi.acm.org/10.1145/1282280.1282326

  109. Reid, M.M., Millar, R.J., Black, N.D.: Second-generation image coding: An overview. ACM Comput. Surv. 29(1), 3–29 (1997). doi:10.1145/248621.248622. URL http://doi.acm.org/10.1145/248621.248622

    Google Scholar 

  110. Rosten, E., Drummond, T.: Machine learning for high-speed corner detection. In: Proceedings of the 9th European Conference on Computer Vision - Volume Part I (ECCV’06), pp. 430–443. Springer, Berlin, Heidelberg (2006). doi:10.1007/ 11744023_34. URL http://dx.doi.org/10.1007/11744023_34

  111. Said, A., Pearlman, W.A.: A new, fast, and efficient image codec based on set partitioning in hierarchical trees. IEEE Trans. Circuits Syst. Video Technol. 6(3), 243–250 (1996). doi:10.1109/76. 499834. URL http://dx.doi.org/10.1109/76.499834

    Google Scholar 

  112. Sensirion AG: Sensirion Digital Humidity and Temperature Sensors (RH&T). http://www.sensirion.com/en/products/humidity-temperature/ (2011)

  113. Shapiro, J.: Embedded image coding using zerotrees of wavelet coefficients. Trans. Signal Process. 41(12), 3445–3462 (1993). doi:10.1109/78.258085. URL http://dx.doi.org/10.1109/78.258085

    Google Scholar 

  114. Skodras, A., Christopoulos, C., Ebrahimi, T.: The JPEG 2000 still image compression standard. IEEE Signal Process. Mag. 18, 36–58 (2001)

    Article  Google Scholar 

  115. Slepian, D., Wolf, J.: Noiseless coding of correlated information sources. IEEE Trans. Inf. Theory 19(4), 471–480 (2006). doi:10.1109/TIT.1973.1055037. URL http://dx.doi.org/10.1109/TIT.1973.1055037

    Google Scholar 

  116. Stitt, G., Vahid, F., Nematbakhsh, S.: Energy savings and speedups from partitioning critical software loops to hardware in embedded systems. ACM Trans. Embed. Comput. Syst. 3(1), 218–232 (2004). doi:10.1145/972627.972637. URL http://doi.acm.org/10.1145/972627.972637

  117. Stojanovic, M.: Underwater acoustic communications: Design considerations on the physical layer. In: Fifth Annual Conference on Wireless on Demand Network Systems and Services, 2008 (WONS 2008). pp. 1–10 (2008). doi:10.1109/WONS.2008.4459349

    Google Scholar 

  118. Svensson, H.: Reconfigurable architectures for embedded systems. Ph.D. thesis, Lund University (2008)

    Google Scholar 

  119. Szeliski, R.: Image alignment and stitching: A tutorial. Found. Trends Comput. Graph. Vis. 2(1), 1–104 (2006). doi:10.1561/0600000009. URL http://dx.doi.org/10.1561/0600000009

  120. Taubman, D.: High performance scalable image compression with ebcot. Trans. Image Process. 9(7), 1158–1170 (2000). doi:10.1109/83.847830. URL http://dx.doi.org/10.1109/83.847830

    Google Scholar 

  121. Telle, N., Luk, W., Cheung, R.: Customising hardware designs for elliptic curve cryptography. In: Pimentel, A., Vassiliadis, S. (eds.) Computer Systems: Architectures, Modeling, and Simulation. Lecture Notes in Computer Science, vol. 3133, pp. 274–283. Springer, Berlin (2004). doi:10.1007/978-3-540-27776-7_ 29. URL http://dx.doi.org/10.1007/978-3-540-27776-7_29

  122. The International Society of Automation: ISA100, Wireless Systems for Automation. www.isa.org/isa100 (2008)

  123. Todman, T., Constantinides, G., Wilton, S., Mencer, O., Luk, W., Cheung, P.: Reconfigurable computing: Architectures and design methods. IEE Proc. Comput. Digit. Tech. 152(2), 193–207 (2005). doi:10.1049/ip-cdt:20045086

    Article  Google Scholar 

  124. Treisman, A., Gelade, G.: A feature-integration theory of attention. Cogn. Psychol. 12(1), 97–136 (1980)

    Article  Google Scholar 

  125. Tsapatsoulis, N., Rapantzikos, K.: Wavelet based estimation of saliency maps in visual attention algorithms. In: Proceedings of the 16th International Conference on Artificial Neural Networks - Volume Part II (ICANN’06), pp. 538–547. Springer, Berlin (2006). doi:10. 1007/11840930_56. URL http://dx.doi.org/10.1007/11840930_56

  126. Tsapatsoulis, N., Rapantzikos, K., Pattichis, C.S.: An embedded saliency map estimator scheme: Application to video encoding. Int. J. Neural Syst. 17(4), 289–304 (2007). URL http://dblp.uni-trier.de/db/journals/ijns/ijns17.html#TsapatsoulisRP07

    Google Scholar 

  127. Tsekoura, I., Selimis, G., Hulzink, J., Catthoor, F., Huisken, J., de Groot, H., Goutis, C.: Exploration of cryptographic ASIP designs for wireless sensor nodes. In: 2010 17th IEEE International Conference on Electronics, Circuits, and Systems (ICECS), pp. 827–830 (2010). doi:10.1109/ICECS.2010.5724640

    Google Scholar 

  128. Tyson, Romas, A., Siti Intan, P., Adiono, T.: A pipelined double-issue mips based processor architecture. In: International Symposium on Intelligent Signal Processing and Communication Systems, 2009 (ISPACS 2009), pp. 583–586 (2009). doi:10.1109/ISPACS.2009.5383771

    Google Scholar 

  129. Urban, F., Follet, B., Chamaret, C., Le Meur, O., Baccino, T.: Medium spatial frequencies, a strong predictor of salience. Cogn. Comput. 3, 37–47 (2011). doi:10.1007/s12559-010-9086-8. URL http://hal.inria.fr/inria-00628096

  130. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004). doi:10.1023/B: VISI.0000013087.49260.fb. URL http://dx.doi.org/10.1023/B:VISI.0000013087.49260.fb

    Google Scholar 

  131. Wagner, R., Nowak, R., Baraniuk, R.: Distributed image compression for sensor networks using correspondence analysis and super-resolution. In: Proceedings of the 2003 International Conference on Image Processing, 2003 (ICIP 2003), vol. 1, pp. I–597–600 (2003). doi:10.1109/ICIP.2003.1247032

    Google Scholar 

  132. Wallace, G.K.: The jpeg still picture compression standard. Commun. ACM 34(4), 30–44 (1991). doi:10.1145/103085. 103089. URL http://doi.acm.org/10.1145/103085.103089

    Google Scholar 

  133. Walther, D., Koch, C.: 2006 special issue: Modeling attention to salient proto-objects. Neural Netw. 19, 1395–1407 (2006). doi:10.1016/j.neunet.2006.10.001. URL http://dl.acm.org/citation.cfm?id=1219169.1219421

    Google Scholar 

  134. Warneke, B., Scott, M., Leibowitz, B., Zhou, L., Bellew, C., Chediak, J., Kahn, J., Boser, B., Pister, K.: An autonomous 16 mm3 solar-powered node for distributed wireless sensor networks. In: Proceedings of IEEE Sensors, 2002, vol. 2, pp. 1510–1515 (2002). doi:10.1109/ICSENS.2002.1037346

    Google Scholar 

  135. Wheeler, F., Pearlman, W.: Spiht image compression without lists. In: Proceedings of the 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2000, vol. 6 (ICASSP ’00), vol.4, pp. 2047–2050 (2000). doi:10.1109/ICASSP.2000.859236

    Google Scholar 

  136. Winbond: Winbond W968D6DKA product page. http://www.winbond.com/hq/enu/ProductAndSales/ProductLines/MobileRAM/PseudoSRAM/W968D6DKA.htmhttp://www.winbond.com/hq/enu/ProductAndSales/ProductLines/MobileRAM/PseudoSRAM/W968D6DKA.htm (2008)

  137. Wu, M., Chen, C.W.: Collaborative image coding and transmission over wireless sensor networks. EURASIP J. Appl. Signal Process. 2007(1), 223–223 (2007). doi:10.1155/2007/70481. URL http://dx.doi.org/10.1155/2007/70481

  138. Wyner, A.D., Ziv, J.: The rate-distortion function for source coding with side information at the decoder. IEEE Trans. Inf. Theory 22, 1–10 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  139. Xilinx: MicroBlaze Soft Processor Core. http://www.xilinx.com/tools/microblaze.htm (2012)

  140. Xilinx: Spartan-3 datasheet. http://www.xilinx.com/support/documentation/data_sheets/ds099.pdf (2012)

  141. Xilinx: Xilinx Artix-7. http://www.xilinx.com/products/silicon-devices/fpga/artix-7/index.htm (2012)

  142. Xilinx: Xilinx XPower. http://www.xilinx.com/products/design_tools/logic_design/verification/xpower.htm (2012). Accessed Nov 2012

  143. Zeidman, B.: Introduction to Verilog. Swiss Creek Publications (2000)

    Google Scholar 

  144. Zeidman, B.: Designing With FPGAs and CPLDs, 1st edn. CRC Press, Boca Raton (2002)

    Google Scholar 

  145. Zhang, J., Orlik, P., Sahinoglu, Z., Molisch, A., Kinney, P.: Uwb systems for wireless sensor networks. Proc. IEEE 97(2), 313–331 (2009). doi:10.1109/JPROC.2008.2008786

    Article  Google Scholar 

  146. ZigBee Alliance: ZigBee Standards. http://www.zigbee.org/Standards/Downloads.aspx (2007)

  147. Zulkifli, M., Yudhanto, Y., Soetharyo, N., Adiono, T.: Reduced stall mips architecture using pre-fetching accelerator. In: International Conference on Electrical Engineering and Informatics, 2009 (ICEEI ’09), vol. 02, pp. 611–616 (2009). doi:10.1109/ICEEI.2009.5254742

    Google Scholar 

  148. Zvikhachevskaya, A., Markarian, G., Mihaylova, L.: Quality of service consideration for the wireless telemedicine and e-health services. In: IEEE Wireless Communications and Networking Conference, 2009 (WCNC 2009), pp. 1–6 (2009). doi:10.1109/WCNC.2009.4917925

    Google Scholar 

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Ang, Lm., Seng, K.P., Chew, L.W., Yeong, L.S., Chia, W.C. (2013). Hardware Technology and Programming Languages for Reconfigurable Devices. In: Wireless Multimedia Sensor Networks on Reconfigurable Hardware. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38203-1_3

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