Cleaning a single-field image or a mosaic

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1.6.4.1 Cleaning a single-field image or a mosaic

The CLEAN algorithm is the most popular and widely-studied method for reconstructing a model image based on interferometer data. It iteratively removes at each step a fraction of the flux in the brightest pixel in a defined region of the current “dirty” image, and places this in the model image. The clean task implements the CLEAN algorithm for single-field data. The user can choose from a number of options for the particular flavor of CLEAN to use.

Often, the first step in imaging is to make a simple gridded Fourier inversion of the calibrated data to make a “dirty” image. This can then be examined to look for the presence of noticeable emission above the noise, and to assess the quality of the calibration by searching for artifacts in the image. This is done using clean with niter=0.

The clean task can jointly deconvolve mosaics as well as single fields, and also has options to do wide-field and wide-band multi-frequency synthesis imaging.

See § 5.3 for an in-depth discussion of the clean task.

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