GNU Astronomy Utilities

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8.2.2 Invoking MakeNoise

MakeNoise will add noise to an existing image. The executable name is astmknoise with the following general template

$ astmknoise [OPTION ...] InputImage.fits

One line examples:

## Add noise with a standard deviation of 100 to image:
$ astmknoise --sigma=100 image.fits

## Add noise to input image assuming a background magnitude (with zeropoint
## magnitude of 0) and a certain instrumental noise:
$ astmknoise --background=-10 -z0 --instrumental=20 mockimage.fits

If actual processing is to be done, the input image is a mandatory argument. The full list of options common to all the programs in Gnuastro can be seen in Common options. The type (see Numeric data types) of the output can be specified with the --type option, see Input/Output options. The header of the output FITS file keeps all the parameters that were influential in making it. This is done for future reproducibility.

-s FLT

The total noise sigma in the same units as the pixel values. With this option, the --background, --zeropoint and --instrumental will be ignored. With this option, the noise will be independent of the pixel values (which is not realistic, see Photon counting noise). Hence it is only useful if you are working on low surface brightness regions where the change in pixel value (and thus real noise) is insignificant.

-b FLT

The background pixel value for the image in units of magnitudes, see Photon counting noise and Flux Brightness and magnitude.

-z FLT

The zeropoint magnitude used to convert the value of --background (in units of magnitude) to flux, see Flux Brightness and magnitude.

-i FLT

The instrumental noise which is in units of flux, see Instrumental noise.


Use the GSL_RNG_SEED environment variable for the seed used in the random number generator, see Generating random numbers. With this option, the output image noise is always going to be identical (or reproducible).


Save the output in the double precision floating point format that was used internally. This option will be most useful if the input images were of integer types.

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