Statistical Scale Space Methods
本文综述了统计尺度空间方法，这些方法通过平滑等手段从含噪数据（如时间序列或数字图像）中提取不同时间或空间尺度上的特征，并介绍了相关应用。
Summary The goal of statistical scale space analysis is to extract scale‐dependent features from noisy data. The data could be for example an observed time series or digital image in which case features in either different temporal or spatial scales would be sought. Since the 1990s, a number of statistical approaches to scale space analysis have been developed, most of them using smoothing to capture scales in the data, but other interpretations of scale have also been proposed. We review the various statistical scale space methods proposed and mention some of their applications.