Low-complexity and energy efficient image compression scheme for wireless sensor networks

被引:61
作者
Lu, Qin [1 ]
Luo, Wusheng [1 ]
Wang, Jidong [1 ]
Chen, Bo [2 ]
机构
[1] Natl Univ Defense Technol, Dept Instrument Sci & Technol, Coll Mechatron Engn & Automat, Changsha 410073, Peoples R China
[2] Natl Univ Defense Technol, Coll Sci, Dept Math & Syst Sci, Changsha 410073, Peoples R China
关键词
image compression; computational complexity; energy consumption; WSNs;
D O I
10.1016/j.comnet.2008.05.006
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Currently most energy-constrained wireless sensor networks are designed with the object of minimizing the communication power at the cost of more computation. To achieve high compression efficiency, the main image compression algorithms used in wireless sensor networks are the high-complexity, state-of-the-art image compression standards, such as JPEG2000. These algorithms require complex hardware and make the energy consumption for computation comparable to communication energy dissipation. To reduce the hardware cost and the energy consumption of the sensor network, a low-complexity and energy efficient image compression scheme is proposed. The compression algorithm in the proposed scheme greatly lowers the computational complexity and reduces the required memory, while it still achieves required PSNR. The proposed implementation scheme of the image compression algorithm overcomes the computation and energy limitation of individual nodes by sharing the processing of tasks. And, it applies transmission range adjustment to save communication energy dissipation. Performance of the proposed scheme is investigated with respect to image quality and energy consumption. Simulation results show that it greatly prolongs the lifetime of the network under a specific image quality requirement. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:2594 / 2603
页数:10
相关论文
共 22 条
[1]   A survey on wireless multimedia sensor networks [J].
Akyildiz, Ian F. ;
Melodia, Tommaso ;
Chowdhury, Kaushik R. .
COMPUTER NETWORKS, 2007, 51 (04) :921-960
[2]   Line-based, reduced memory, wavelet image compression [J].
Chrysafis, C ;
Ortega, A .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2000, 9 (03) :378-389
[3]   Efficient sign coding and estimation of zero-quantized coefficients in embedded wavelet image codecs [J].
Deever, AT ;
Hemami, SS .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2003, 12 (04) :420-430
[4]  
DEPEDRI A, 2003, AUTONOMOUS INTELLIGE
[5]   An application-specific protocol architecture for wireless microsensor networks [J].
Heinzelman, WB ;
Chandrakasan, AP ;
Balakrishnan, H .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2002, 1 (04) :660-670
[6]  
Heinzelman WB., 2000, THESIS MIT
[7]  
Malvar H., 1992, SIGNAL PROCESSING LA
[8]   Biorthogonal and nonuniform lapped transforms for transform coding with reduced blocking and ringing artifacts [J].
Malvar, HS .
IEEE TRANSACTIONS ON SIGNAL PROCESSING, 1998, 46 (04) :1043-1053
[9]   Distributed compression in a dense microsensor network [J].
Pradhan, SS ;
Kusuma, J ;
Ramchandran, K .
IEEE SIGNAL PROCESSING MAGAZINE, 2002, 19 (02) :51-60
[10]   Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks [J].
Qing, Li ;
Zhu, Qingxin ;
Wang, Mingwen .
COMPUTER COMMUNICATIONS, 2006, 29 (12) :2230-2237