An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN
P.Samundiswary1, H.Rekha2
1P.Samundiswary*, Department of Electronics Engineering, Pondicherry University, Pondicherry, India.
2H.Rekha, Department of Electronics Engineering, Pondicherry University, Pondicherry, India.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 2761-2768 | Volume-8 Issue-12, October 2019. | Retrieval Number: L25641081219/2019©BEIESP | DOI: 10.35940/ijitee.L2564.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For the past two decades, wavelet based image compression algorithms for Wireless Sensor Network (WSN) has gained broad attention than that of the spatial based image compression algorithms. In that, Dual Tree Complex Wavelet Transforms (DTCWT) has provided better results in terms of image quality and high compression rate. However, the selection of DTCWT based image compressions for various WSN based applications is not practically suitable, due to the major limitations of WSN such as, low bandwidth, low energy consumption and storage space. Therefore, an attempt has been made in this paper to develop image compression through simulation by considering the modified block based pass parallel Set Partitioning In Hierarchical Trees (SPIHT) with Double Density Dual Tree Complex Wavelet Transform (DDDTCWT) for compressing the WSN based images. In addition, bivariate shrink method is also adopted with the DDDTCWT to obtain better image quality within less computation time. It is observed through simulation results that above mentioned proposed technique provides better performance than that of existing compression technique
Keywords: Bivariate Shrink Method, Double Density Wavelets, Image Compression, Set Partitioning in Hierarchical Trees, Wireless Sensor Networks .
Scope of the Article: Wireless Sensor Networks