As discussed above (MakeCatalog), NoiseChisel (Gnuastro’s signal detection tool, see NoiseChisel) does not produce any catalog of the detected objects. However, most other common tools in astronomical data-analysis (for example SExtractor107) merge the two processes into one. Gnuastro’s modularized methodology is therefore new to many experienced astronomers and deserves a short review here. Further discussion on the benefits of this methodology can be seen in Akhlaghi .
To simplify catalog production from a raw input image in Gnuastro, NoiseChisel’s output (see NoiseChisel output) can be directly fed into MakeCatalog. This is good when no further customization is necessary and you want a fast/simple. But the modular approach taken by Gnuastro has many benefits that will become more apparent as you get more experienced in astronomical data analysis and want to be more creative in using your valuable data for the exciting scientific project you are working on. In short the reasons for this modularity can be classified as below:
As an example, if the parameter you want to measure over one profile is not provided by the developers of MakeCatalog. You can simply open this tiny little program and add your desired calculation easily. This process is discussed in Adding new columns to MakeCatalog. However, if making a catalog was part of NoiseChisel, it would require a lot of energy to understand all the steps and internal structures of that large program (the most complex in Gnuastro) in order to add desired parameter in a catalog.
Here is an example of doing both: suppose you have images in various broad band filters at various resolutions and orientations. The image of one color will thus not lie exactly on another or even be in the same scale. However, it is imperative that the same pixels be used in measuring the colors of galaxies.
To solve the problem, NoiseChisel can be run on the reference image to generate the labeled image. After wards, the labeled image can be warped into the grid of the other color (using Warp). MakeCatalog will then generate the same catalog for both colors (with the different labeled images). It is currently customary to warp the images to the same pixel grid, however, modification of the scientific dataset is very harmful for the data and creates correlated noise. It is much more accurate to do the transformations on the labeled image.