Description

Overview

The skymatch step can be used to compute sky values of input images or it can be used to compute corrections that need to be applied to images such as to “equalize” (match) sky background in input images. When running skymatch step in a matching mode, skymatch compares total signal levels in the overlap regions (instead of doing this comparison on a per-pixel basis, cf. mrs_imatch step) of a set of input images and computes the signal offsets for each image that will minimize the residuals across the entire set in the least squares sence. This comparison is performed directly on input images without resampling them onto a common grid. By default the sky value computed for each image is recorded, but not actually subtracted from the images.

Assumptions

When matching sky background code needs to compute bounding polygon intersections in world coordinates. Therefore, input images need to have valid WCS.

Algorithm

The skymatch step provides several methods for constant sky background value computations.

First method, called 'localmin' essentially is an enhanced version of the original sky subtraction method used in older astrodrizzleversions. This method simply computes the mean/median/mode/etc. value of the “sky” separately in each input image. This method was upgraded to be able to use DQ flags and user supplied masks to remove “bad” pixels from being used for sky statistics computations. Values different from zero in user-supplied masks indicate “good” data pixels.

In addition to the classical 'localmin', two other methods have been introduced: 'globalmin' and 'match', as well as a combination of the two – 'globalmin+match'.

  • The 'globalmin' method computes the minimum sky value across all input images. That single sky value is then considered to be the background in all input images.

  • The 'match' algorithm computes constant (within an image) value corrections to be applied to input images such that the mismatch in computed background values between all pairs of images is minimized in the least squares sence. For each pair of images background mismatch is computed only in the regions in which the two images intersect.

    This makes 'match' sky computation algorithm particularly useful for “equalizing” sky values in large mosaics in which one may have only (at least) pair-wise intersection of images without having a common intersection region (on the sky) in all images.

  • The 'globalmin+match' algorithm combines 'match' and 'globalmin' methods. It uses 'globalmin' algorithm to find a baseline sky value common to all input images and the 'match' algorithm to “equalize” sky values among images.

Step Arguments

The skymatch step has the following optional arguments:

General sky matching parameters: * skymethod: A str value indicating sky computation algorithm to be used.

Allowed values: {'local', 'global', 'match', 'global+match'} (Default = 'global+match')
  • match_down: A boolean that specifies whether the sky differences should be subtracted from images with higher sky values (match_down = True) to match the image with the lowest sky or sky differences should be added to the images with lower sky values to match the sky of the image with the highest sky value (match_down = False). (Default = True)

    Note

    This setting applies only when skymethod parameter is either 'match' or 'global+match'.

  • subtract: A boolean indicating whether computed sky background values

    be subtracted from image data. (Default = False)

Image’s bounding polygon parameters: * stepsize: An integer number indicating spacing between vertices of the

image’s bounding polygon. Default value of None creates bounding polygons with four vertices corresponding to the corners of the image.

Sky statistics parameters: * skystat A string describing statistics to be used for sky background

value computations. Supported values are: ‘mean’, ‘mode’, ‘midpt’, and ‘median’ (Default = ‘mode’)
  • lower An optional float value indicating lower limit of usable pixel values for computing the sky. This value should be specified in the units of the input image(s). (Default = None)
  • upper An optional float value indicating upper limit of usable pixel values for computing the sky. This value should be specified in the units of the input image(s). (Default = None)
  • nclip: A non-negative integer number of clipping iterations to use when computing the sky value. (Default = 5)
  • lsig: Lower clipping limit, in sigma, used when computing the sky value. (Default = 4.0)
  • usig: Upper clipping limit, in sigma, used when computing the sky value. (Default = 4.0)
  • binwidth: Bin width, in sigma, used to sample the distribution of pixel brightness values in order to compute the sky background statistics. (Default = 0.1)

Limitations and Discussions

Primary reason for introducing “sky match” algorithm was to try to equalize the sky in large mosaics in which computation of the “absolute” sky is difficult due to the presence of large diffuse sources in the image. As discussed above, the skymatch step accomplishes this by comparing “sky values” in input images in the overlap regions (that is common to a pair of images). Quite obviously the quality of sky “matching” will depend on how well these “sky values” can be estimated. We use quotation marks around sky values because for some image “true” background may not be present at all and the measured sky may be the surface brightness of large galaxy, nebula, etc.

Here is a brief list of possible limitations/factors that can affect the outcome of the matching (sky subtraction in general) algorithm:

  • Since sky subtraction is performed on flat-fielded but not distortion corrected images, it is important to keep in mind that flat-fielding is performed to obtain uniform surface brightness and not flux. This distinction is important for images that have not been distortion corrected. As a consequence, it is advisable that point-like sources be masked through the user-supplied mask files. Values different from zero in user-supplied masks indicate “good” data pixels. Alternatively, one can use upper parameter to limit the use of bright objects in sky computations.
  • Normally, distorted flat-fielded images contain cosmic rays. This algorithm does not perform CR cleaning. A possible way of minimizing the effect of the cosmic rays on sky computations is to use clipping (nclip > 0) and/or set upper parameter to a value larger than most of the sky background (or extended source) but lower than the values of most CR pixels.
  • In general, clipping is a good way of eliminating “bad” pixels: pixels affected by CR, hot/dead pixels, etc. However, for images with complicated backgrounds (extended galaxies, nebulae, etc.), affected by CR and noise, clipping process may mask different pixels in different images. If variations in the background are too strong, clipping may converge to different sky values in different images even when factoring in the “true” difference in the sky background between the two images.
  • In general images can have different “true” background values (we could measure it if images were not affected by large diffuse sources). However, arguments such as lower and upper will apply to all images regardless of the intrinsic differences in sky levels.

Reference Files

This step does not require any reference files.