Satellite Detection in ACS/HST Images

We present a unique process by which satellite trails can be detected and accurately masked within individual chips of an Advanced Camera for Surveys (ACS) Wide Field Channel (WFC) image using Python. Satellites are sporadic transient events which are very hard to predict, so it is necessary to detect them post-priori. Fortunately, we have developed a tool. Tested by the manually checked Hubble Frontier Fields (HFF) datasets we are able to verify that our new process does a complete job with a low false positive rate. Here, we also present an automated process for creating a mask that will contain the entire trail and allow it to be included in the Data Quality (DQ) array of HST images to inform users and their software where trails traverse the image. This code is publicly available through the acstools (<a href='https://acstools.readthedocs.io/en/latest/'>https://acstools.readthedocs.io/en/latest/</a>) package and can be easily installed by users through the astroconda (<a href='http://astroconda.readthedocs.io/en/latest/'>http://astroconda.readthedocs.io/en/latest/</a>) anaconda channel.