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In recent year, the Forward and Inverse Discrete Wavelet Transform (FDWT/IDWT) (S.Mallet, 1999) has been widely used as an alternative to the existing time-frequency representations such as DFT and DCT. It has become a powerful tool in many areas, such as image compression and analysis, texture discrimination, fractal analysis, pattern recognition and so on. The recent and future developments of high definition digital video and the diversity of the terminals had led to consider a multi-resolution codec. In this context, the FDWT/IDWT as well as the others computational functions such as Motion Estimation (ME) are required to be scalable and flexible to support rich multimedia applications and adapt to the fast changing of standards requirement. In this background, a universal, extremely scalable and flexible computational architecture which can adapt to variable workload would be more and more important and suitable for the multimedia application in the future. In the literature, there have been several proposals devoted to the hardware implementation of FDWT/IDWT. Some proposals(M.A.Trenas et al., 2002) (et al, 2002) (Lee & Lim, 2006)(Ravasi, 2002)(P.Jamkhandi et al., 2000)(Tseng et al., 2003)addressed the importance of flexibility and proposed programmable DWT architectures based on two types: VLSI or FPGA architecture. The VLSI architectures have large limitations in terms of flexibility and scalability compared to the FPGA architectures. Even though some recent solutions proposed programmable and scalable for either variable wavelet filters(Olkkonen & T.Olkkonen, 2010) (Lee & Lim, 2006) or the structure of FDWT, they remind, in addition to their cost, dedicated to specifics algorithms and cannot be adapted to future solutions. In another hand, the existing FPGA architectural solutions are mainly ASIC like architectures and use external off-the-shelf memory components which represent a bottleneck for data access. The possibility of parallelizing the processing elements offered by FPGAs associated to a sequential access to data and bandwidth limitations do not enhance the overall computing throughput. The very powerful commercial VLIW digital signal processor obtains its performance thanks to a double data-path with a set of arithmetic and logic operators with a possibility of parallel executions and a wide execution pipeline. However, these performances are due to a high frequency working clock. Even though these DSP has a parallel but limited access to a set of instructions, the data memory access remains sequential. The performance requirement is paid by high circuit complex and power consumption. Most of work focuses on the reuse of devices likes FPGAs for different applications or different partitions of one applications. In order to square up these needs, we propose a novel DWT architecture and implementation method. The proposed architecture can support multi-standard by reconfiguring the 2

A Scalable Architecture for Discrete Wavelet Transform on FPGA-Based System