星际云结构分析的模板匹配方法
Template matching method for the analysis of interstellar cloud structure
摘要：
星际介质的结构在大尺度上可以用它的全局统计（例如功率谱）来表征，在小尺度上可以用单个核的性质来表征。人们对中等尺度结构的兴趣越来越大，因此开发了许多分析非线性结构的方法。我们描述了通用模板匹配（TM）方法的地图分析的应用。我们的目的是表明，它提供了一种快速和仍然相对稳健的方式来识别细长结构或其他图像特征。我们提出了一个TM算法的地图分析的实现。与滚动Hough变换（RHT），以前用于识别非线性结构的方法之一的结果进行了比较。我们说明的方法，将其应用到赫歇尔表面亮度数据。TM方法的性能被认为是可比的RHT，但TM似乎是更强大的输入参数，例如，那些与选定的空间尺度。TM的小的修改使一个目标结构在不同的大小和强度水平。除了细长的功能，我们证明了使用TM也确定其他类型的结构的可能性。TM方法是数据质量控制、探索性数据分析甚至图像数据中结构的定量分析的可行工具。
英文摘要：
The structure of interstellar medium can be characterised at large scales in terms of its global statistics (e.g. power spectra) and at small scales by the properties of individual cores. Interest has been increasing in structures at intermediate scales, resulting in a number of methods being developed for the analysis of filamentary structures. We describe the application of the generic template-matching (TM) method to the analysis of maps. Our aim is to show that it provides a fast and still relatively robust way to identify elongated structures or other image features. We present the implementation of a TM algorithm for map analysis. The results are compared against rolling Hough transform (RHT), one of the methods previously used to identify filamentary structures. We illustrate the method by applying it to Herschel surface brightness data. The performance of the TM method is found to be comparable to that of RHT but TM appears to be more robust regarding the input parameters, for example, those related to the selected spatial scales. Small modifications of TM enable one to target structures at different size and intensity levels. In addition to elongated features, we demonstrate the possibility of using TM to also identify other types of structures. The TM method is a viable tool for data quality control, exploratory data analysis, and even quantitative analysis of structures in image data.
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