A computational architecture for discrete wavelet transform using lifting scheme
Fabián Cabrera Sánchez, Carlos A. Fajardo, Carlos A. Angulo, Oscar Mauricio Reyes, Charles A. Bouman · 2014
The Discrete Wavelet Transform (DWT) is an important technique for signal analysis, compressing and denoising due to its excellent locality in the time-frequency domain. The DWT is developed by convolutions which demand both a large number of mathematical operations and a large amount of storage. The lifting scheme reduces both computational and storage requirements. We have developed a computational architecture for inverse DWT using the lifting scheme. The design was developed in VHDL and then implemented into a Virtex 5 FPGA. We aim to reach a high throughput and reduce the design area. The architecture takes 3L + N(1-0.5L) clock cycles to compute L levels of 1D reconstruction for data of size N. Some comparisons suggest that our work could be faster than previous works.