Memory Reduction Methodology for Distributed-Arithmetic-Based DWT/IDWT Exploiting Data Symmetry

In this brief, we show that by exploiting the inherent symmetry of the discrete wavelet transform (DWT) algorithm and consequently storing only the nonrepetitive combinations of filter coefficients, the size of required memory can be significantly reduced. Subsequently, a memory-efficient architecture for DWT/inverse DWT is proposed. It occupies 6.5-mm² silicon area and consumes 46.8-muW power at 1 MHz for 1.2 V using 0.13-mum standard cell technology.