基于提升的DWT图像处理算法的可重构硬件实现

S. Khanfir, M. Jemni
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引用次数: 9

摘要

近年来提出了一种新的离散小波变换快速算法——提升算法。与基于卷积的方法相比,这种新方案具有许多优点。例如,它非常适合并行化。在本文中,我们提出了两个新的基于fpga的基于DWT提升方案的并行实现。第一个实现采用流水线、并行处理和数据重用来提高算法的速度。在第二个体系结构中,引入了一个控制器来根据目标环境中的可用硬件资源动态部署适当数量的克隆。这两种架构都能够实时处理大尺寸输入图像或多帧图像。在Xilinx Virtex-5 FPGA环境下进行的仿真验证了我们所做的工作的实际效率。事实上,第一种架构给出了289 MHz的工作频率,第二种架构展示了控制器的能力,可以确定在目标FPGA环境中成功部署独立克隆所需的真正可用资源,并并行处理任务。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reconfigurable Hardware Implementations for Lifting-Based DWT Image Processing Algorithms
A novel fast scheme for Discrete Wavelet Transform (DWT) was lately introduced under the name of lifting scheme. This new scheme presents many advantages over the convolution-based approach. For instance it is very suitable for parallelization. In this paper we present two new FPGA-based parallel implementations of the DWT lifting-based scheme. The first implementation uses pipelining, parallel processing and data reuse to increase the speed up of the algorithm. In the second architecture a controller is introduced to deploy dynamically a suitable number of clones accordingly to the available hardware resources on a targeted environment. These two architectures are able of processing large size incoming images or multi-framed images in real-time. The simulations driven on a Xilinx Virtex-5 FPGA environment has proven the practical efficiency of our contribution. In fact, the first architecture has given an operating frequency of 289 MHz, and the second architecture demonstrated the controllerpsilas capabilities of determining the true available resources needed for a successful deployment of independent clones, over a targeted FPGA environment and processing the task in parallel.
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