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Low Complexity Hardware Architectures for Wavelet Transforms: A Survey

机译:小波变换的低复杂性硬件架构:调查

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Presently, the major focus is on developing techniques to efficiently decrease hardware expenditure as well as hardware complications while realizing the requirements for a real-time system. The enhancement of Discrete Wavelet Transforms DWT's hardware modelling is still a relatively novel subject of research. Such areas comprise developing an effective hardware acceleration of the implementation of the DWT of the JPEG2000 standard, to construct a practical model and to deal with the computational and communication energy limitations of the image compression system. This paper emphasizes a comprehensive survey to develop necessary solutions to enhance the potential and capacity of DWT's computation-intensive nature algorithm implementation, particularly for low power image compression applications. The paper focuses on the major factors in order to lower the DWT principal energy consuming phase, given the energy consumption of the whole wavelet based image compression. These factors may possibly encompass some hardware-based features, such as basic coding features, low memory requirement, and low computational load. In combination with this research, other paper areas are also being investigated.
机译:目前,主要重点是开发技术,以有效地减少硬件支出以及硬件并发症,同时实现实时系统的要求。离散小波的增强变换DWT的硬件建模仍然是一个相对小说的研究主题。这些区域包括开发JPEG2000标准DWT的实现的有效硬件加速度,以构建实际模型并处理图像压缩系统的计算和通信能量限制。本文强调了一个全面的调查,以制定必要的解决方案,以提高DWT计算密集型性质算法实现的潜力和容量,特别是对于低功率图像压缩应用。鉴于整个小波的图像压缩的能量消耗,本文侧重于主要因素以降低DWT主能耗阶段。这些因素可能包含一些基于硬件的功能,例如基本编码特征,低内存要求和低计算负载。结合本研究,还正在调查其他纸张区域。

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