International Journal of Innovative Technology and Exploring Engineering (IJITEE) ISSN: 2278-3075, Volume-8 Issue-12, October 2019 2762 Published By: Blue Eyes Intelligence Engineering & Sciences Publication Retrieval Number: L25641081219/2019©BEIESP DOI:10.35940/ijitee.L2564.1081219 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 . I. INTRODUCTION In recent years, image based way of communication is receiving a lot of attention in various applications of WSN domain [1]. However, the number of redundancies present inside the images engages huge storage space and in turn increases the energy consumption during WSN based communication. With the intention that, to surmount the unwanted redundancies, image compression is the best choice. By removing the redundancies using image compression, the memory space, bandwidth and energy consumption needed to store and transmit the images are decreased effectively. Usually, the architecture of WSN has huge quantity of sensor nodes to capture images. Each node from WSN has the capacity to reduce/resize and communicate the original input images to the user location. In that case, lossy image compression methods are chosen for WSN to provide high compression ratio with better image features. But, most of the lossy image compression algorithms implemented so far, for the sensor nodes are inappropriate to Revised Manuscript Received on October 05, 2019. * Correspondence Author P.Samundiswary*,Department of Electronics Engineering, Pondicherry University, Pondicherry, India. Email: samundiswary_pdy@yahoo.com H.Rekha,Department of Electronics Engineering, Pondicherry University, Pondicherry, India. Email:saathvekha16@gmail.com retain the original features of the input image and also in reducing the computation time [2]. For instance, Chew et al. [3] have provided the evaluation of different image compression algorithms and analyzed their performance in terms of storage space, computational complexity and compressed image quality. Also, it is found through the several literature surveys that, Set Partitioning In Hierarchical Tree (SPIHT) provides high compression ratio and less computation complexity than other compression algorithms [4-6]. Later, Kumar and et al. [7] have projected a new approach based on Singular Value Decomposition (SVD). In this work, the author combined the SVD along with hybrid of Discrete Cosine Transform (DCT) and Block Truncation Coding (BTC) to get the better performance of compression in terms of Mean Square Error (MSE) and PSNR, than that of the existing JPEG (Joint Photographic Experts Group) and SPIHT image compression techniques. Then, Nasri et al. [8] have presented a better adaptive image compression method that guarantees a considerable reduction in computational load and energy consumption as well as communication of image with better image quality. Here, the overall computation time is reduced by distributing the processing tasks among the clusters. After that, Ghorbel et al. [9] have described the importance of discrete cosine and discrete wavelet transform in image compression. Further, they gave the clear view about the performance comparison of these two transforms with various existing image compression algorithms in different WSN transmission scenario. Later, Ghorbel et al. [10] have extended their work by considering the additional parameter called energy consumption and concluded that the effectiveness of the DWT is superior when compared to the DCT in terms of computation time and image quality. Followed by Ghorbel, Ma et al. , several researchers [11] have reviewed different multimedia based compression and transmission techniques by considering the resource constrained platform with respect to the performance metric namely energy efficiency. Despite, many compression techniques, only a small number of techniques have considered and utilized for practical applications to face the energy constraint problems. It is clear from the previous research works that the three basic image compression techniques such as JPEG (DCT), SPIHT and JPEG2000 (Embedded block coding using optimized truncation) are suitable for multimedia compression. The pros and cons of these three algorithms are analysed and compared by using their compression efficiency, storage space and computational complexity. An Efficient Pass Parallel SPIHT based Image Compression using Double Density Dual Tree Complex Wavelet Transform for WSN P.Samundiswary, H.Rekha