Linear Feature detection¶
Description of the algorithm’s implementation, execution parameters and performance is availible in
Bektesevic & Vinkovic, 2017, Linear feature detection algorithm for astronomical surveys - I. Algorithm description
availible at arxiv.org/abs/1612.04748
This module contains all the basic functionality required to execute the linear feature detector interactively or in a sequential batch-like processing setup.
The module requires that all the required data exists and is linked to as
described in the
Central construct of this module is the
class which keeps track of the execution parameters and targeted data.
Broadly speaking the detection is a three step process:
- Removal of all known objects
- Detection of bright linear features
- Detection of dim linear features.
Each step is individually configurable through the params dictionaries of the class.
It is instructive to read the docstring of
process_field() to see the steps algorithm does. For
its implementation or mode details see
module of the package.
DetectTrails is not SDSS data agnostic but the
processing functionality in
lfd.detecttrails.processfield is. That way
this module can be used to run on other data given that the images are in FITS
format and that the catalog for each image is also given as a header table of a
FITS file. There should be one such fits catalog per image.
Other catalog sources are possible but not impemented. It is instructive to see
removestars module which should contain examples of
old deprecated CSV catalog functionality.