论文标题
使用OTSU的方法分开蓝色云和红色序列以进行图像分割
Separating the blue cloud and the red sequence using Otsu's method for image segmentation
论文作者
论文摘要
观察到的颜色双峰允许将星系分类为两个不同的类：“蓝色云”和“红色序列”。这种分类通常是使用颜色的经验剪切和其他缺乏固体数学理由的星系特性进行的。我们提出了一种使用OTSU的阈值技术进行图像分割的方法，将“蓝色云”中的星系和“红色序列”分开。我们表明，这种技术对选择的选择不敏感。它为基于阶层内方差的最小化和阶层间方差的最大化，为红色和蓝色星系的分类提供了强大的无参数方法。我们还基于OTSU改进分类的方法应用了一种迭代的Triclass阈值技术。已知星系颜色取决于星系的恒星质量和光度。我们通过在许多独立的恒星质量垃圾箱和绝对幅度垃圾箱中采用这些方法来获得颜色 - 冠状质量平面和颜色吸收幅度平面之间的两个种群之间的分隔线。
The observed colour bimodality allows a classification of the galaxies into two distinct classes: the `blue cloud' and the `red sequence'. Such classification is often carried out using empirical cuts in colour and other galaxy properties that lack solid mathematical justifications. We propose a method for separating the galaxies in the `blue cloud' and the `red sequence' using Otsu's thresholding technique for image segmentation. We show that this technique is insensitive to the choice of binning. It provides a robust and parameter-free method for the classification of the red and blue galaxies based on the minimization of the intra-class variance and maximization of the inter-class variance. We also apply an iterative triclass thresholding technique based on Otsu's method to improve the classification. The galaxy colour is known to depend on the stellar mass and the luminosity of galaxies. We obtain the dividing lines between the two populations in the colour-stellar mass plane and the colour-absolute magnitude plane by employing these methods in a number of independent stellar mass bins and absolute magnitude bins.
