Low power hardware-based image compression solution for wireless camera sensor networks

In this paper, we present and evaluate a hardware solution for user-driven and packet loss tolerant image compression, especially designed to enable low power image compression and communication over wireless camera sensor networks (WCSNs). The proposed System-on-Chip is intended to be designed as a hardware coprocessor embedded in the camera sensor node. The goal is to relieve the node microcontroller of the image compression tasks and to achieve high-speed and low power image processing. The interest of our solution is twofold. First, compression settings can be changed at runtime (upon reception of a request message sent by an end user or according to the internal state of the camera sensor node). Second, the image compression chain includes a (block of) pixel interleaving scheme which significantly improves the robustness against packet loss in image communication. We discuss in depth the internal hardware architecture of the encoder chip which is planned to reach high performance running in FPGAs and in ASIC circuits. Synthesis results and relevant performance comparisons with related works are presented. We study a low power hardware solution for image compression in wireless camera sensor network. The goal is to relieve the node microcontroller of the image compression tasks and to achieve low-power image processing. We discuss the internal hardware architecture of the proposed encoder circuit and its implementation. We provide relevant comparisons with related solutions.

[1]  G.M. Aly,et al.  JPEG encoder for low-cost FPGAs , 2007, 2007 International Conference on Computer Engineering & Systems.

[2]  Ioannis Pitas,et al.  Chaotic Mixing of Digital Images and Applications to Watermarking , 1996 .

[3]  Nicolas Krommenacker,et al.  Energy-Efficient Transmission of Wavelet-Based Images in Wireless Sensor Networks , 2007, EURASIP J. Image Video Process..

[4]  Shanq-Jang Ruan,et al.  A computationally efficient high-quality cordic based DCT , 2006, 2006 14th European Signal Processing Conference.

[5]  Deborah Estrin,et al.  Cyclops: in situ image sensing and interpretation in wireless sensor networks , 2005, SenSys '05.

[6]  Kamin Whitehouse,et al.  Achieving stable network performance for wireless sensor networks , 2008, SenSys '08.

[7]  Luca Benini,et al.  Hardware-assisted data compression for energy minimization in systems with embedded processors , 2002, Proceedings 2002 Design, Automation and Test in Europe Conference and Exhibition.

[8]  Sergio Bampi,et al.  Multiplierless and fully pipelined JPEG compression soft IP targeting FPGAs , 2007, Microprocess. Microsystems.

[9]  Tughrul Arslan,et al.  2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), Beijing, China, May 19-23, 2013 , 2013, International Symposium on Circuits and Systems.

[10]  Bo Chen,et al.  Low-complexity and energy efficient image compression scheme for wireless sensor networks , 2008, Comput. Networks.

[11]  B. Carminati,et al.  Computer Standards & Interfaces , 2009 .

[12]  Trac D. Tran,et al.  Fast multiplierless approximations of the DCT with the lifting scheme , 2001, IEEE Trans. Signal Process..

[13]  Mohd Fadzli Mohd Salleh,et al.  Golomb Coding Implementation in FPGA , 2008 .

[14]  Wendi B. Heinzelman,et al.  A Survey of Visual Sensor Networks , 2009, Adv. Multim..

[15]  Solomon W. Golomb,et al.  Run-length encodings (Corresp.) , 1966, IEEE Trans. Inf. Theory.

[16]  Sesh Commuri,et al.  Run time compression of image data in wireless sensor networks , 2010, 2010 International Conference on Networking, Sensing and Control (ICNSC).

[17]  Constantinos E. Goutis,et al.  Efficient high-performance implementation of JPEG-LS encoder , 2008, Journal of Real-Time Image Processing.

[18]  Vincent Lecuire,et al.  Error resilient image communication with chaotic pixel interleaving for wireless camera sensors , 2008, REALWSN '08.

[19]  Xinkai Chen,et al.  A VLSI design of sensor node for wireless image sensor network , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[20]  Frédéric Amiel,et al.  FPGA vs. ASIC for low power applications , 2006, Microelectron. J..

[21]  Naoki Wakamiya,et al.  Challenging issues in visual sensor networks , 2009, IEEE Wireless Communications.

[22]  Margaret Martonosi,et al.  Data compression algorithms for energy-constrained devices in delay tolerant networks , 2006, SenSys '06.

[23]  Lan-Rong Dung,et al.  An ultra-low-power image compressor for capsule endoscope , 2006, Biomedical engineering online.

[24]  Shie-Jue Lee,et al.  A JPEG Chip for Image Compression and Decompression , 2003, J. VLSI Signal Process..

[25]  S. Golomb Run-length encodings. , 1966 .

[26]  J. Vitter,et al.  Practical Implementations of Arithmetic Coding , 1991 .

[27]  Athanasios Kakarountas,et al.  Efficient High-Performance ASIC Implementation of JPEG-LS Encoder , 2007, 2007 Design, Automation & Test in Europe Conference & Exhibition.

[28]  Cristian Duran Faundez Transmission d'images sur les réseaux de capteurs sans fil sous la contrainte de l'énergie , 2009 .

[29]  B. Heyne,et al.  A low-power and high-quality implementation of the discrete cosine transformation , 2007 .

[30]  Eugenio Culurciello,et al.  CMOS image sensors for sensor networks , 2006 .

[31]  Gadiel Seroussi,et al.  On adaptive strategies for an extended family of Golomb-type codes , 1997, Proceedings DCC '97. Data Compression Conference.

[32]  Jinsang Kim,et al.  Low-power multiplierless DCT architecture using image correlation , 2004, IEEE Trans. Consumer Electron..

[33]  Anthony Rowe,et al.  CMUcam3: An Open Programmable Embedded Vision Sensor , 2007 .

[34]  Alhussein A. Abouzeid,et al.  Error resilient image transport in wireless sensor networks , 2006, Comput. Networks.

[35]  Anthony Vetro,et al.  Energy efficient JPEG 2000 image transmission over wireless sensor networks , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[36]  Ioannis Papaefstathiou,et al.  Heavily Reducing WSNs' Energy Consumption by Employing Hardware-Based Compression , 2009, ADHOC-NOW.

[37]  Luigi Ferrigno,et al.  Balancing computational and transmission power consumption in wireless image sensor networks , 2005, IEEE Symposium on Virtual Environments, Human-Computer Interfaces and Measurement Systems, 2005..

[38]  Jean-Marie Moureaux,et al.  Fast zonal DCT-based image compression for Wireless Camera Sensor Networks , 2010, 2010 2nd International Conference on Image Processing Theory, Tools and Applications.

[39]  Sergio Bampi,et al.  A FPGA based design of a multiplierless and fully pipelined JPEG compressor , 2005, 8th Euromicro Conference on Digital System Design (DSD'05).

[40]  Ian F. Akyildiz,et al.  Sensor Networks , 2002, Encyclopedia of GIS.

[41]  G.S. Moschytz,et al.  Practical fast 1-D DCT algorithms with 11 multiplications , 1989, International Conference on Acoustics, Speech, and Signal Processing,.

[42]  Ian F. Akyildiz,et al.  A survey on wireless multimedia sensor networks , 2007, Comput. Networks.

[43]  Sujit Dey,et al.  A hardware/software reconfigurable architecture for adaptive wireless image communication , 2002, Proceedings of ASP-DAC/VLSI Design 2002. 7th Asia and South Pacific Design Automation Conference and 15h International Conference on VLSI Design.