NoiseChisel will detect and segment signal in noise producing a multi-extension labeled image, ready for input into MakeCatalog to generate a catalog or other processing. The executable name is astnoisechisel with the following general template
$ astnoisechisel [OPTION ...] InputImage.fits
One line examples:
## Detect signal in input.fits: $ astnoisechisel input.fits ## Detect signal assuming input has 4 channels along first dimension ## and 1 along the second. Also set the regular tile size to 100 along ## both dimensions: $ astnoisechisel --numchannels=4,1 --tilesize=100,100 input.fits
If NoiseChisel is to do processing (for example you don’t want to get help, or see the values to each input parameter), an input image should be provided with the recognized extensions (see Arguments). NoiseChisel shares a large set of common operations with other Gnuastro programs, mainly regarding input/output, general processing steps, and general operating modes. To help in a unified experience between all of Gnuastro’s programs, these operations have the same command-line options, see Common options for a full list. Since the common options are thoroughly discussed there, they are no longer reviewed here. You can see all the options with a short description on the command-line with the --help option, see Getting help.
NoiseChisel’s input image may contain blank elements (see Blank pixels). Blank elements will be ignored in all steps of NoiseChisel. Hence
if your dataset has bad pixels which should be masked with a mask image,
please use Gnuastro’s Arithmetic program (in particular its
where operator) to convert those pixels to blank pixels before
running NoiseChisel. Gnuastro’s Arithmetic program has bitwise operators
helping you select specific kinds of bad-pixels when necessary.
A convolution kernel can also be optionally given. If a value (file name) is given to --kernel on the command-line or in a configuration file (see Configuration files), then that file will be used to convolve the image prior to thresholding. Otherwise a default kernel will be used. The default kernel is a 2D Gaussian with a FWHM of 2 pixels truncated at 5 times the FWHM. This choice of the default kernel is discussed in Section 3.1.1 of Akhlaghi and Ichikawa . See Convolution kernel for kernel related options.
NoiseChisel defines two tessellations over the input (see Tessellation). This enables it to deal with possible gradients in the input dataset and also significantly improve speed by processing each tile on different threads. The tessellation related options are discussed in Processing options. In particular, NoiseChisel uses two tessellations (with everything between them identical except the tile sizes): a fine-grained one with smaller tiles (mainly used in detection) and a more larger tiled one which is used for multi-threaded processing. The common Tessellation options described in Processing options define all parameters of both tessellations, only the large tile size for the latter tessellation is set through the --largetilesize option. To inspect the tessellations on your input dataset, run NoiseChisel with --checktiles.
Usage TIP: Frequently use the options starting with --check. Depending on what you want to detect in the data, you can often play with the parameters/options for a better result than the default parameters. You can start with --checkdetection and --checksegmentation for the main steps. For their full list please run:
$ astnoisechisel --help | grep check
In the sections below, NoiseChisel’s options are classified into three general classes to help in easy navigation. General NoiseChisel options mainly discusses the options relating to input and those that are shared in both detection and segmentation. Options to configure the detection are described in Detection options and Segmentation options we discuss how you can fine-tune the segmentation of the detections. Finally in NoiseChisel output the format of NoiseChisel’s output is discussed. The order of options here follow the same logical order that the respective action takes place within NoiseChisel (note that the output of --help is sorted alphabetically).
|• General NoiseChisel options:||General NoiseChisel preprocessing.|
|• Detection options:||Configure detection in NoiseChisel.|
|• Segmentation options:||Configure segmentation in NoiseChisel.|
|• NoiseChisel output:||NoiseChisel’s output format.|