An energy efficient image compression scheme for wireless multimedia sensor network using curve fitting technique
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Wireless multimedia sensor network (WMSN) comprising of miniature sensor nodes is capable of processing multimedia data traffic such as still images and video from the environment. There is a wide range of applications which get benefited from such network. Unprocessed multimedia transmission is always expensive in terms of processing power, storage, and bandwidth. So, data processing is a challenge in WMSN. Exploring low-overhead data compression technique is a solution towards this problem. In this work we propose an energy saving image compression technique for WMSN using curve fitting technique considering the application of post-disaster situation analysis through image capturing of the affected area. Upon employing the method on the macroblocks of sensory image, curve fitting coefficients are generated and transmitted towards the sink thereby saves energy by transmitting reduced volume of data. Finally the design feasibility along with simulation results including statistical analysis is presented to evaluate efficacy of the scheme in terms of two conflicting parameters viz. energy consumption and peak signal to noise ratio. The comparative results confirm our scheme’s supremacy in WMSN application domain over existing methods.
KeywordsWireless multimedia sensor network Image compression Curve fitting Routing Contiki OS
- 7.Pal, T., & Bit, D. S. (2015). A new CFA based image compression technique for energy-starved wireless multimedia sensor network. In Proceedings on 12th international conference INDICON, 2015 (pp. 1–6). IEEE.Google Scholar
- 12.Jessintha, D., Reghu, C., & Raj, V. (2010). A energy efficient, architectural reconfiguring DCT implementation of JPEG images using vector scaling. In Proceedings on international conference ICSIP, 2010 (pp. 59–62). IEEE.Google Scholar
- 13.Qin, L., Wusheng, L., & Xiangbin, Y. (2009). Collaborative in-network processing of LT based image compression algorithm in WMSNs. In Proceedings on international conference ETCS, 2009 (pp. 839–843). IEEE.Google Scholar
- 14.Banerjee, R., & Bit, D. S. (2015). Low-overhead image compression in WMSN for post disaster situation analysis. In Proceedings on 9th international conference ANTS, 2015 (pp. 1–6). IEEE.Google Scholar
- 15.Hassan, K. K., Ngah, U. K., & Salleh, M. F. M. (2012). The most proper wavelet filters in low-complexity and an embedded hierarchical image compression structures for wireless sensor network implementation requirements. In Proceedings on international conference on control system, computing and engineering, 2012 (pp. 137–142). IEEE.Google Scholar
- 16.Eldin, Z. H., Elhosseini, A. M., & Ali, A. H. (2015). A modified listless strip based SPIHT for wireless multimedia sensor networks. Computers and Electrical Engineering, 56, 519–532.Google Scholar
- 17.Nasri, M., Helali, A., Sghaier, H., & Maaref, H. (2010). Adaptive image transfer for wireless sensor network (WSNs). In Proceedings on 5th international conference DTIS, 2010 (pp 1–7). IEEE.Google Scholar
- 21.Faundez, D. C., Lecuire, V., & Lepage, F. (2011). Tiny block-size coding for energy-efficient image compression and communication in wireless camera sensor networks. Signal Processing: Image Communication, 26, 466–481.Google Scholar
- 22.Pal, T., Bandhopadhyay, S., & Bit, D. S. (2015). Energy-saving image transmission over WMSN using block size reduction technique. In Proceedings international symposium on nanoelectronic and information systems, 2015 (pp. 41–45). IEEE.Google Scholar
- 25.Gupta, K., Bansal, M., & Chaudhury, S. (2011). A compression scheme for handwritten patterns based on curve fitting. In Proceedings 11th international conference ICDAR, 2011 (pp. 1116–1119). IEEE.Google Scholar
- 28.Song, Y., Hu, J., Yang, X., Fu, J., & Xie, X. (2010). A method for data stream processing based on curve fitting. In Proceedings on 2nd international conference ICSPS, 2010 (pp. 542–546). IEEE.Google Scholar
- 30.Arif, S., Mansor, S., & Karim, A. H. (2012). Lossless compression of fluoroscopy medical images using correlation and the combination of run-length and Huffman coding. In Proceedings on international conference of biomedical engineering and sciences (pp. 759–762). IEEE.Google Scholar
- 31.MicaZ wireless measurement system. www.openautomation.net/uploadsproductos/micaz_datasheet.pdf. Accessed June 15, 2016.
- 32.MSP430x2xx Family user’s guide. www.ti.com/lit/ug/slau144j/slau144j.pdf. Accessed January 21, 2017.
- 33.ARM architecture reference model. www.scss.tcd.ie/~waldroj/3d1/arm_arm.pdf. Accessed January 18, 2017.
- 35.Labrodor, A. M., & Wightman, M. P. (2009). Topology control in wireless sensor networks. Berlin: Springer.Google Scholar
- 36.Sheng, B., Tan, C. C., Li, Q., & Mao, W. (2007). An approximation algorithm for data storage placement in sensor networks. In Proceedings on international conference on wireless algorithms, systems and applications (pp. 71–78). IEEE.Google Scholar