The International Arab Journal of Information Technology (IAJIT)


VLSI-Oriented Lossy Image Compression Approach using DA-Based 2D-Discrete

 In  this  paper,  we  introduced  a  Discrete  Wavelet  Tra nsform  (DWT)  based  VLSI-oriented  lossy  image  compre ssion  approach,  widely  used  as  the  core  of  digital  image  compression.  Here,  Distributed  Arithmetic  (DA)  tech nique  is  applied  to  determine  the  wavelet  coefficients,  so  that  the  num ber  of  arithmetic  operation  can  be  reduced  substant ially.  As  well,  the  compression rate is enhanced with the aid of introd ucing RW block that blocks some of the coefficients obtained from the high  pass  filter  to  zero.    Subsequently,  Differential  Pu lse-Code  Modulation  (DPCM)  and  huffman-encoding  are   applied  to  acquire  the  binary  sequence  of  the  image.  The  functional  si mulation  of  each  module  is  presented  as  well  as  the   performance  of  each  module  is  widely  analyzed  with  gate  required,  clock   cycles  required,  power,  processing  rate,  and  processing  time.  From  the  analysis,  it  is  found  that  the  DCM  module  requires  more  gates  to  do  the  transformation  process  compare d  to  other  modules.  Eventually, the proposed compression approach is co mpared with the existing methods in terms of processor area and power.  Comparative  result  shows  that  the  proposed  method  o ffers  good  performance  in  power-efficiency  corresponding  to  0.328  mW/chip than the prior methods.   

[1] Andra K., Chakrabarti C., and Acharya T., A VLSI Architecture for Lifting2Based Forward and Inverse Wavelet Transform, IEEE Transaction Signal Process , vol. 50, no. 4, pp. 9662977, 2002.

[2] Artyomov E. and Yadid2Pecht O., Adaptive Multiple2Resolution CMOS Active Pixel Sensor, IEEE Transaction on Circuits System I: Regular Papers , vol. 53, no. 10, pp. 217822186, 2006.

[3] Baili J., Lahouar S., Hergli M., Amimi A., and Besbes K., Application of the Discrete Wavelet Transform to Denoise GPR Signals, in Proceedings of ISCCSP , pp. 124, 2006.

[4] Bandyopadhyay A., Lee J., Robucci R., and Hasler P., Matia: A Programmable 80 W/frame CMOS Block Matrix Transform Imager Architecture, IEEE Journal Solid-State Circuits , vol. 41, no. 3, pp. 6632672, 2006.

[5] Bhuyan M., Amin N., Madesa M., and Islam M., FPGA Realization of Lifting Based Forward Discrete Wavelet Transform for JPEG 2000, International Journal of Circuits, Systems and Signal Processing , vol. 1, no. 2, pp. 1242129, 2007.

[6] Cao X., Xie Q., Peng C., Wang Q., and Yu D., An Efficient VLSI Implementation of Distributed Architecture for DWT, in Proceedings of the IEEE 8 th Workshop on Multimedia Signal Processing , Victoria, pp. 3642 367, 2006.

[7] Calderbank A., Wavelet Transforms that Map Integers to Integers, Applied and Computational Harmonic Analysis , vol. 5, no. 3, pp. 3322369, 1998.

[8] Chakrabarti C., Vishwanath M., and Owens R., Architectures for Wavelet Transforms: A Survey, Journal VLSI Signal Process , vol. 14, no. 2, pp. 1712192, 1996.

[9] Chao W. and Peng C., Efficient Architecture for 22Dimensional Discrete Wavelet Transform with Novel Lifting Algorithm, Chinese Journal of Electronics , vol. 19, no. 1, pp. 126, 2010.

[10] Chen S., Bermak A., Yan W., and Martinez D., Adaptive2Quantization Digital Image Sensor for Low2Power Image Compression, IEEE Transaction Circuits System I: Regular Papers , vol. 54, no. 1, pp. 13225, 2007.

[11] Chen S., Bermak A., and Wang Y., A CMOS Image Sensor with on2Chip Image Compression Based on Predictive Boundary Adaptation and Memoryless QTD Algorithm, IEEE Transactions on Very Large Scale Integration Systems , vol. 19, no. 4, pp. 5382547, 2011.

[12] Chopade N., Ghatol A., and Kolte M., Efficient Image Compression and Transmission using SPECK, in Proceedings of SPIT-IEEE Colloquium and International Conference , India, vol. 1, pp. 1562160, 2007.

[13] Davis G. and Nosratinia A., Wavelet2Based Image Coding: an Overview, in Proceedings of Applied and Computational Control, Signals, and Circuits , New York, vol. 1, pp. 2052269, 1998.

[14] Daubechies I. and Sweldens W., Factoring Wavelet Transforms into Lifting Steps, Journal Fourier Analysis Applications , vol. 4, no. 3, pp. 2472269, 1998.

[15] Dhulap S. and Nalbalwar S., Image Compression Based on IWT, IWPT & DPCM2 IWPT, International Journal of Engineering Science and Technology , vol. 2, no. 12, pp. 74132 7422, 2010.

[16] Farahani M. and Eshghi M., Implementing a New Architecture of Wavelet Packet Transform on FPGA, in Proceedings of the 8 th WSEAS International Conference on Acoustics & Music: Theory & Applications , Canada, pp. 37241, 2007.

[17] Gupta A., Dyer M., Hirsch A., Nooshabadi S., and Taubman D., Design of a Single Chip Block Coder for the EBCOT Engine in JPEG2000, in Proceedings of the 48 th Midwest Symposium on Circuits and Systems , pp. 63266, 2005.

[18] Huang C., Tseng P., and Chen L., VLSI Architecture for Forward Discrete Wavelet Transform Based on B2Spline Factorization, Journal of VLSI Signal Processing Systems for VLSI-Oriented Lossy Image Compression Approach using DA-Based 2D-Discrete Wavelet 67 Signal, Image and Video Technology , vol. 40, no. 3, pp. 3432353, 2005.

[19] Huang C., Seng P., and Chen L., Analysis and VLSI Architecture for 12D and 22D Discrete Wavelet Transform, IEEE Transactions on Signal Processing , vol. 53, no. 4, pp. 157521586, 2005.

[20] Huang C., Tseng P., and Chen L., Flipping Structure: an Efficient VLSI Architecture for Lifting2Based Discrete Wavelet Transform, IEEE Transaction Signal Processing , vol. 52, no. 4, pp. 108021089, 2004.

[21] Huang C., Tseng P., and Chen L., VLSI Architecture for Discrete Wavelet Transform Based on B2Spline Factorization, in Proceedings of IEEE Workshop Signal Processing System , Taiwan, pp. 3462350, 2003.

[22] Jeng Y., Hsu S., and Chang Y., Entropy Improvement for Fractal Image Coder, International Arab Journal of Information Technology , vol. 9, no. 5, pp. 4032410, 2012.

[23] Kharate G., Ghatol A., and Rege P., Image Compression using Wavelet Packet Tree ICGST International Journal on Graphics, Vision and Image Processing , vol. 5, no. 7, pp. 37240, 2005.

[24] Len2Salas W., Balkir S., Sayood K., Schemm N., and Hoffman M., A CMOS Imager with Focal Plane Compression Using Predictive Coding, IEEE Journal Solid-State Circuits , vol. 42, no. 11, pp. 255522572, 2007.

[25] Lin C., Zhang B., and Zheng Y., Packed Integer Wavelet Transform Constructed by Lifting Scheme, IEEE Transactions on Circuits and Systems for Video Technology , vol. 10, no. 8, pp. 149621501, 2000.

[26] Lin Z., Hoffman M., Schemm N., Leon2Salas W., and Balkir S., A CMOS Image Sensor for Multi2 Level Focal Plane Image Decomposition, IEEE Transaction Circuits System: Regular Papers , vol. 55, no. 9, pp. 256122572, 2008.

[27] Liu K., Wang K., Li Y., and Wu C., A Novel VLSI Architecture for Real2Time Line2Based Wavelet Transform using Lifting Scheme, Journal of Computer Science and Technology , vol. 22, no. 5, pp. 6612672, 2007.

[28] Maamoun M., Namane A., Neggazi M., Beguenane R., Meraghni A., and Berkani D., VLSI Design for High2Speed Image Computing using Fast Convolution2Based Discrete Wavelet Transform, in Proceedings of the World Congress on Engineering , London, vol. I, pp. 12 5, 2009.

[29] Mallat S., A Theory for Multiresolution Signal Decomposition: The Wavelet Representation, IEEE Transaction on Pattern Analysis and Machine Intelligence , vol. 11, no. 7, pp. 6742693, 1989.

[30] Munteanu A., Cornelis J., and Cristea P., Wavelet2Based Lossless Compression of Coronary Angiographic Images, IEEE Transactions on Medical Imaging , vol. 18, no. 3, pp. 2722281, 1999.

[31] Nebout C., Moury G., and Blamont J., Status of Onboard Image Compression for CNES Space Missions, in Proceedings of SPIE , Applications of Digital Image Processing XXII , vol. 3808, pp. 2422256, 1999.

[32] Nilchi A., Aziz J., and Genov R., Focal2Plane Algorithmically2Multiplying

[ CMOS Computational Image Sensor, IEEE Journal Solid-State Circuits , vol. 44, no. 6, pp. 18292 1839, 2009.

[33] Pillai L., Huffman Coding, available at: plication_notes/xapp616.pdf, last visited 2003.

[34] Pujar J. and Kadlaskar L., A New Lossless Method of Image Compression and Decompression using Huffman Coding Techniques, Journal of Theoretical and Applied Information Technology , vol. 15, no.1, pp. 18223, 2010.

[35] Rao C. and Latha M., A Novel VLSI Architecture of Hybrid Image Compression Model Based on Reversible Blockade Transform, in Proceedings of World Academy of Science, Engineering and Technology , USA, vol. 52, pp. 101621022, 2009.

[36] Song M., Entropy Encoding in Wavelet Image Compression, in Proceedings of Representations, Wavelets and Frames, Applied and Numerical Harmonic Analysis , Birkh user Boston, pp. 2932311, 2007.

[37] Sweldens W., The Lifting Scheme: A Custom2 Design Construction of Bi2Orthogonal Wavelets, Applied and Computational Harmonic Analysis , vol. 3, no. 15, pp. 1862200, 1996.

[38] Trenas M., Lopez J., and Zapata E., FPGA Implementation of Wavelet Packet transform with Reconfigurable Tree Structure, in Proceedings of the 26 th Euromicro Conference , Spain, vol. 1, pp. 2442251, 2000.

[39] Uzun I. and Amira A., Real2Time 22D Wavelet Transform Implementation for HDTV Compression, Real-Time Imaging , vol. 11, no. 2, pp. 1512165, 2005. 68 The International Arab Journal of Information Technology, Vol. 11, No. 1, January 2014 Devangkumar Shah obtained his Bs degree in electrical engineering from Gujarat University, India in 1999. Then he obtained his Ms degree in microprocessor system applications from the MS University of Baroda, India in 2008. Currently, he is a assistant professor at the School of Engineering, R K University, India. His specializations include blue tooth network, networking, and virtual reality. His curre nt research interests are digital signal and image processing, microprocessor, embedded systems and VLSI. Chandresh Vithlani obtained his Bs degree in electronics and communication engineering from Gujarat University, India in 1991. Then he obtained his Ms degree in electronics and communication engineering from Gujarat University, India in 1998 and PhD degree in electronics communication from Gujarat University in the year 2006. Currently, he is working as an associate professor in the Department of Electronics Communication Engineering, Government. Engineering College, India. He has published number of papers in national and international conferences and journals. His current research areas of interests a re microprocessor, embedded systems, digital signal an d image processing.