Implementasi Transformasi Wavelet Diskret Haar pada FPGA Xilinx Spartan-3E
Abstrak
Penelitian ini membahas implementasi transformasi wavelet diskret Haar yang efisien dan akurat dengan melakukan pemilihan struktur filter bank dan format data yang tepat. Ada tiga struktur filter bank, yang meliputi satu struktur filter bank polifase dan dua struktur filter bank lattice serta tiga format data, yang meliputi dua format data fixed point dan satu format data single precision floating point, yang digunakan dalam implementasi transformasi wavelet diskret Haar yang diteliti pengaruhnya terhadap penggunaan resources. Selain itu pada penelitian ini juga dibahas mengenai pengaruh tingkat dekomposisi terhadap penggunaan resources FPGA. Tingkat dekomposisi divariasikan dari satu tingkat dekomposisi sampai dengan enam tingkat dekomposisi untuk kemudian diteliti pengaruhnya terhadap resources FPGA. Implementasi transformasi wavelet diskret Haar dilakukan pada Field Programmable Gate Array (FPGA) Xilinx Spartan-3E danditujukan untuk pemrosesan isyarat suara. Dengan menggunakan struktur filter bank lattice dan format data fixed point, implementasi transformasi wavelet diskret Haar dengan enam tingkat dekomposisi hanya memerlukan slice sebanyak 5% dan memiliki akurasi hasil sebesar 98,9%.
Referensi
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.
© Jurnal Nasional Teknik Elektro dan Teknologi Informasi, di bawah Lisensi Creative Commons Atribusi-BerbagiSerupa 4.0 Internasional.
2.png)
