SPIHT algorithm and the wavelet coefficients is analyzed.
分析了SPIHT算法和小波系数的特点。
参考来源 - 基于最优小波包的改进型SPIHT图像压缩算法The key of that method is the wavelet coefficients statistical model.
该方法的关键在于小波系数模型的选取。
参考来源 - 基于小波变换图像去噪研究The new concept of instantaneous intensity factor and instantaneous flatness factor based on wavelet coefficients together with sampling schemes for multi-scale coherent eddy structures are represented in this paper.
提出了基于子波系数的瞬时强度因子、瞬时平坦因子的概念,及检测多尺度相干结构的准则。
参考来源 - 湍流边界层多尺度结构间歇性检测和控制的实验研究·2,447,543篇论文数据，部分数据来源于NoteExpress
Furthermore, through the maximum likelihood used for evaluating three parameters of wavelet coefficients' probability model, the adaptive algorithm is derived in the article.
而且本文通过极大似然法估计小波系数概率模型中的三个参数，使算法达到自适应。
Have analyzed properties of wavelet coefficients obtained from an image through wavelet transform, and discussed how to select wavelet basis to optimize wavelet coefficients.
分析了图像小波变换后小波系数的特征，讨论了优化小波系数的小波基选择问题。
The quality of image processing can be significantly improved by exploiting the correlation among image wavelet coefficients and modeling the statistics for these coefficients.
研究图像小波系数间的统计相关性并建立适当的模型，可以显著提高图像处理的质量。
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