Implementasi Transformasi Wavelet Diskret Haar pada FPGA Xilinx Spartan-3E
Abstract
This paper discusses the efficient and accurate implementation of the discrete Haar Wavelet Transform (HWT) by selection of the best fit filter bank structure and data format. There are three filter bank structures including one polyphase and two lattice filter bank structure and also three data formats including two fixed point and one single precision floating point data format which are used in implementation of discrete Haar wavelet transform are discussed in relation with the using of FPGA resources. Beside that this paper also discuss about the effect of decomposition level on utilization of FPGA resources. The decomposition level is varied from 1st to 6th level and then its effect on the FPGA resources will be observed. The implementation of the Haar wavelet transform is performed on Field Programmable Gate Array (FPGA) Xilinx Spartan-3E and it is intended for processing of voice signals. By using the lattice filter bank structure and fixed-point data format, the implementation of Haar Wavelet Transform with six decomposition levels only require 5% of FPGA’s slice and give accuracy 98.9%.
References
M. Angelopoulou, K. Masselos, P. Cheung and Y. Andreopoulos, "A Comparison of 2-D Discrete Wavelet Transform Computation Schedules on FPGA," 2006.
Q. Huang, Y. Wang and S. Chang, "High Performance FPGA Implementation of Discrete Wavelet Transform for Image Processing," 2011.
M. Guarisco, X. Zhang, H. Rabah and W. Serge, "An Efficient Implementation of Scalable Architecture for Discrete Wavelet Transform On FPGA," in IEEE, 2007.
M. Katona, A. Pizurica, N. Teslic, V. Kovacevic and W. Philips, "FPGA Designand Implementation of a Wavelet Domain Video Denoising System".
P. Gupta and S. K. Lenka, "A Novel VLSI of Architecture of High Speed 1D Discrete Wavelet Transform," International Journal of Electrical and Electronic Engineering (IJEEE), vol. 3, no. I, pp. 79-85, 2013.
H. Sahoolizadeh and A. Keshavarz, "A FPGA Implementation of Neural / Wavelet Face Detection System," Australian Journal of Basic and Applied Science, pp. 379-388, 2010.
A. Benkrid, K. Benkrid and D. Crookes, "Designand Implementation of a Generic 2-D Orthogonal Discrete Wavelet Transform on FPGA," in 11th Annual IEEE Symposium of Field Programmable CustomComputing Machine (FCCM'03), 2003.
K. H. Talukder and K. Harada, "Haar Wavelet Based Approach for Image Compression and Quality Assessment of Compressed Image," IAENG International Journal of Applied Mathematics,2006.
R. M. Jiang and D. Crookes, "FPGA Implementation of 3D Discrete Wavelet Transform for Real-Time Medical Imaging," IEEE, 2007.
A. Ahmad, P. Nicholl and B. Krill, "Dynamic Parial Reconfiguration of 2-D Haar Wavelet Transfrom (HWT) for Face Recognition System".
J. Chilo and T. Lindblad, "Hardware Implementation of 1D Wavelet Transform on an FPGA for Infrasound Signal Classification," in IEEE Transaction on Nuclear Science Vol. 55, 2008.
M. Vetterli and J. Kovacevic, Wavelet and Suband Coding, New Jersey: Prentice Hall PTR, 2007.
M. Steinbuch and M. Van de Molengraft, Wavelet Theory and Application a Literature Study, Eindhoven: Eindhoven University Technology Department of Mechanical Engineering Control System Group, 2005.
R. Wood, J. McAllister, G. Lightbody and Y. Yi, FPGA-based Implementation of Signal Processing Systems, Wiltshire, United Kingdom: John Wiley & Sons, 2008.
P. P. Chu, FPGA Prototyping By Verilog Examples (Xilinx Spartan-3 Version), New Jersey: John Willey & Sons, 2008.
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