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A real-time wavelet vector quantization algorithm and its VLSI architecture

机译:实时小波矢量量化算法及其VLSI架构

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A real-time wavelet image compression algorithm using vector quantization and its VLSI architecture are proposed. The proposed zerotree wavelet vector quantization (WVQ) algorithm focuses on the problem of how to reduce the computation time to encode wavelet images with high coding efficiency. A conventional wavelet image-compression algorithm exploits the tree structure of wavelet coefficients coupled with scalar quantization. However, they can not provide the real-time computation because they use iterative methods to decide zerotrees. In contrast, the zerotree WVQ algorithm predicts in real-time zero-vector trees of insignificant wavelet vectors by a noniterative decision rule and then encodes significant wavelet vectors by the classified VQ. These cause the zerotree WVQ algorithm to provide the best compromise between the coding performance and the computation time. The noniterative decision rule was extracted by the simulation results. Moreover, the zerotree WVQ exploits the multistage VQ to encode the lowest frequency subband, which is generally known to be robust to wireless channel errors. The proposed WVQ VLSI architecture has only one VQ module to execute in real-time the proposed zerotree WVQ algorithm by utilizing the vacant cycles for zero-vector trees which are not transmitted. And the VQ module has only L+1 processing elements (PEs) for the real-time minimum distance calculation, where the codebook size is L. L PEs are for Euclidean distance calculation and a PE is for parallel distance comparison.
机译:提出了一种基于矢量量化的实时小波图像压缩算法及其VLSI架构。提出的零树小波矢量量化(WVQ)算法着眼于如何减少编码效率高的小波图像编码的计算时间问题。常规的小波图像压缩算法利用小波系数的树形结构结合标量量化。但是,它们不能提供实时计算,因为它们使用迭代方法来确定零树。相反,零树WVQ算法通过非迭代决策规则在不重要的小波矢量的实时零矢量树中进行预测,然后通过分类的VQ对重要的小波矢量进行编码。这些导致零树WVQ算法在编码性能和计算时间之间提供最佳折衷。仿真结果提取了非迭代决策规则。此外,零树WVQ利用多级VQ对最低频率子带进行编码,这通常已知对无线信道错误具有鲁棒性。提出的WVQ VLSI体系结构只有一个VQ模块,可以通过利用未传输的零向量树的空闲周期来实时执行提出的零树WVQ算法。 VQ模块仅具有L + 1个处理元件(PE)用于实时最小距离计算,其中码本大小为L。LPE用于欧氏距离计算,而PE用于并行距离比较。

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