Polymorphic DWT Based on Lifting Method for Dynamic Image Compression

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2017 by IJETT Journal
Volume-50 Number-2
Year of Publication : 2017
Authors : M. Nagabushanam, Dr P Kumar


M. Nagabushanam, Dr P Kumar "Polymorphic DWT Based on Lifting Method for Dynamic Image Compression", International Journal of Engineering Trends and Technology (IJETT), V50(2),103-113 August 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Discrete wavelet transform (DWT) is increasingly being used for advanced image and video processing, and computer graphics. DWT forms a significant part of the computations in the image/video compression algorithms and many image compression schemes based on DWT architecture are reported. Several hardware architectures reported in the literature fail to address the requirements of applications having a dynamic aspect. In this article, a Polymorphic Wavelet (Poly?DWT) architecture is presented with dynamic hardware allocation and hardware reusability features.

[1] D. Lie, K. Chae, and S. Mukhopadhyay, "Analysis of the Performance, Power, and Noise Characteristics of a CMOS Image Sensor With 3-D Integrated Image Compression Unit," IEEE Trans. Compon. Packag.Manuf. Technol., vol.4, no.2, Feb. 2014, pp.198-208.
[2] A. Pande and J. Zambreno , “Poly-DWT: polymorphic wavelet hardware support for dynamic image compression,” ACM Transactions on Embedded Computing Systems., vol. 11, no.1, Mar. 2012, pp.6.
[3] Yusong Hu, and ChingChuen Jong, "A Memory-Efficient High-Throughput Architecture for Lifting-Based Multi-Level 2-D DWT," IEEE Trans. Signal Process., vol. 61, no.20, Oct. 2013, pp.4975-4987.
[4] M.E.Angelopoulou et al. “Implementation and comparison of the 5/3 lifting 2D discrete wavelet transform computation schedules on FPGAs,” J Signal Process Sys., vol. 51, no.1, Apr. 2008, pp.3–21.
[5] A. Darji, et al., "Dual-Scan Parallel Flipping Architecture for a Lifting-Based 2-D Discrete Wavelet Transform," IEEE Trans. Circuits Syst.II., vol.61, no.6, June.2014, pp.433-437.
[6] M. Alam, et al. "Efficient distributed arithmetic based DWT architecture for multimedia applications," System-on-Chip for Real-Time Applications, 2003. Proceedings. The 3rd IEEE International Workshop on , vol., no.,2003 pp.333-336
[7] S.J. Choi and J.W.Woods, “Motion-compensated 3-D subband coding of video,” IEEE Trans. Image process., vol.8, no.2, Feb 1999, pp.155–167.
[8] D. Stroobandt, et al., “Reconfigurable hardware for a scalable wavelet video decoder and its performance requirements”, In Computer Systems: Architectures, Modeling, and Simulation, D. Stroobandt, et al, Springer, Volume 3133, 2004, pp 203-212.
[9] A. Das, A. Hazra, and S. Banerjee, “An Efficient Architecture for 3-D Discrete Wavelet Transform,” IEEE Trans. Circuits Syst. Video Technol. , vol.20, no.2, Feb. 2010, pp.286–296.
[10] I. Daubechies and W. Sweldens, “Factoring wavelet transforms into lifting steps,” J. Fourier Anal. Appl., vol. 4, no.3, Sep. 1998, pp. 247–269.
[11] K.A. Kotteriet al., “A comparison of hardware implementations of the biorthogonal 9/7 DWT: convolution versus lifting,” IEEE Trans. Circuits Syst.II., vol. 52, no.5, May. 2005, pp. 256–260.
[12] R. Lavanya, and B. Saranya, “High Speed, Low Complexity, Folded, Polymorphic Wavelet Architecture Using Reconfigurable Hardware,” Int. J. Comput. Appl. T., vol. 2, no.5, June 2010, pp. 1-4.
[13] S.G.Mallat, “A theory for multiresolution signal decomposition: the wavelet representation,” IEEE Trans. Pattern Anal. Mach. Intell., vol.11, no.7, July. 1989, pp.674–693.
[14] R. Qiu and W. Yu, “An efficient quality scalable motion-JPEG2000 transmission scheme” Washington University, Department Of Computer Science, WUCS-01-37,2001, pp. 1-9.
[15]A.Said, and W.A.Pearlman, “An image multiresolution representation for lossless and lossy compression,” IEEE Trans. Image Process., vol. 5, no.9, Sep. 1996, pp.1303–1310.
[16] J.M.Shapiro, “Embedded image coding using zerotrees of wavelet coefficients,” IEEE Trans. Signal Process., vol. 41, no.12, Dec. 1993, pp.3445–3462.
[17] T.Y Sung, H.CHsin, Y.-S. Shieh, and C.-W. Yu, "Low-Power Multiplierless 2-D DWT and IDWT Architectures Using 4-tap Daubechies Filters," Parallel and Distributed Computing, Applications and Technologies, 2006. PDCAT `06. Seventh International Conference on , vol., no.,2006, pp.185-190
[18] Jian-aoLian; Yonghui Wang, "Energy Preserving QMF for Image Processing," IEEE Trans. Image Process., vol.23, no.7, July 2014, pp.3166,3178.
[19] P. Kumar, A. Mittal and P. Kumar, “Fusion of thermal infrared and visible sprectrum video for robust surveillance”. Proceedings of the 5th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP `06), Volume 4338, 2006, pp 528-539
[20] W.Yang, et al., “4-D wavelet-based multiview video coding,” IEEE Trans. Circuits Syst. Video Technol., vol.16, no.11, Nov 2006, pp. 1385-1396.
[21] D. Tay, “Rationalizing the coefficients of popular biorthogonal wavelet filters,” IEEE Trans. Circuits Syst. Video Techno., vol. 10, no.6, Sep. 2000, pp.998–1005.
[22] C.-T. HUANG, P.-C. TSENG,, AND L.-G. CHEN, “VLSI architecture for discrete wavelet transform based on B-spline factorization”. In Proceedings of the IEEE Workshop on Signal Processing Systems (SIPS).IEEE,2003, pp.346–350.
[23] M. Martina, AND G. Masera, “Multiplierless, folded 9/7 - 5/3 wavelet VLSI architecture,” IEEE Trans.Circuits Syst. II., vol. 54, no.9, Sep. 2007, pp.770–774.
[24] C. Christopoulos, A. Skodras, and T. Ebrahimi, “The JPEG2000 still image coding system: an overview," IEEE Trans. Consum. Electron., vol.46, no.4, Nov 2000, pp.1103-1127.
[25] X. Zhao, A.T. Erdogan, and T. Arslan, "High-Efficiency Customized Coarse-Grained Dynamically Reconfigurable Architecture for JPEG2000 IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol.21, no.12, Dec. 2013, pp.2343, 2348.

DWT, poly-DWT, dynamic hardware allocation, lifting, Le-Gall, Daubechies, 5/3, 9/7, coefficients.