Design of DWT based Image Compression Technique for Wireless Sensor Network Applications


  • Prayoth Tanasan
  • Kumsawat Srikotr



Wireless sensor networks, Image compression, Wavelet transform


In this paper, we propose an efficient image compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We use MATLAB simulation to evaluate the image compression technique called “Discrete Wavelet Transform Skipped High Pass Sub-band (DWT-SHPS). Furthermore, we have implemented an image compression using DWT-SHPS technique on a low-cost single board computer. The evaluation is performed under the wavelet compression framework from the view point of quality of image and data compression ratio. Different combinations of parameters and transformation levels have been compared against the JPEG compression standard. The experimental results indicate that the SHPS technique is close to the performance of JPEG standard. It efficient and has low complexity with less memory requirements in the hardware implementation.




[1] Kumsawat P., Attakitmongcol K., and Srikaew A., (2015). A New Optimum Signal Compression Algorithm Based on Neural Networks for WSN. Proceedings of the World Congress on Engineering 2015, Vol. 1, pp. 151-156, London, U.K

[2] Chew, L.W., Ang, L.M. & Seng, K.P. (2008). Survey of image compression algorithms in wireless sensor networks, Proceedings of the International Symposium on Information Technology, (ITSim 2008), Kuala Lumpur, Malaysia.

[3] Paek, J., & Ko, J. (2017). K-Means Clustering-Based Data Compression Scheme for Wireless Imaging Sensor Networks, IEEE Systems Journal, 99, pp. 1-11.

[4] Nasri, M., Helali, A., Sghaier, H., & Maaref, H. (2010). Energy-efficient wavelet image compression in Wireless Sensor Network, Proceedings of the International Conference on Communication in Wireless Environments and Ubiquitous Systems: New Challenges (ICWUS), Sousse, Tunisia.

[5] Mostefa, B., & Sofiane, B.H., (2016). Adaptive image compression in wireless sensor networks, Proceedings of the International Conference on Internet Technology and Secured Transactions (ICITST), Vol. 1, pp. 437-441.

[6] Patel, N., & Chaudhary, J. (2017). Energy efficient WMSN using image compression: A survey, Proceedings of the International Conference on Innovative Mechanisms for Industry Applications (ICIMIA), Vol. 1, pp. 4124-128.

[7] Chaudhari, R.E., & Dhok, S.B. (2014). Wavelet transformed based fast fractal image compression, Proceedings of the International Conference on Circuits, Systems, Communication and Information Technology Applications (CSCITA), Mumbai, India.

[8] Wu, M.S. (2014). Genetic algorithm based on discrete wavelet transformation for fractal image compression, Journal of Visual Communication and Image Representation, 25, pp. 1835-1841.

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