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I. Introduction

4. Cautionary Notes

c. Image Atlas


  1. Depth-of-Coverage Variations
  2. Low Coverage Areas
  3. Astrometric Bias with Respect to Source Catalog
  4. The intensity units of Atlas Image pixels are Digital Numbers (DN)—Photometric Calibration
  5. Background (frame-overlap) Matching
  6. Atlas Image Artifacts
  7. Saturation
  8. Missed (Unmasked) Saturation
  9. Over-tagging of Outliers in Complex Regions
  10. Low-flux Banding Artifacts
  11. Effective Size of a "point-source" in an Atlas Image

i. Depth-of-Coverage Variations

Global and local variations in the depth-of-coverage are expected from the nominal survey design (section VI.2). However, there are regions where the depth-of-coverage varies considerably due to the exclusion of "bad" input frames and individual pixels when generating the Image Atlas. This could be due to contamination from the moon, cosmic rays, and/or other outliers (e.g., induced by fast moving objects), or bad quality frames in general. The latter are usually associated with elevated noise or degraded image quality caused by excursions in spacecraft tracking. For details on the frame selection process, see section V.2.c. A general description of the construction of the depth-of-coverage maps and the physical meaning of pixel values therein is given in section II.3.d.

ii. Low Coverage Areas

Examples of Atlas Images with low depth-of-coverage are shown in section VI.2.c. An immediate consequence for regions with low depth-of-coverage (covered effectively <~ 6 times) is that the temporal pixel-outlier rejection process becomes unreliable. Even though robust estimators were used in this method, they are still relatively "noisy" when the number of samples in the stack was low. Strictly speaking, no temporal pixel-outlier rejection is performed for depths-of-coverage ≤ 4. This criterion avoided throwing away too many good pixels during the coaddition process, with the caveat of increasing the number of unreliable or spurious detections (cosmic rays, fast moving object trails, and other transients). Note that the Source Catalog selection process explicitly excluded extractions from regions with a depth-of-coverage ≤ 4.

iii. Astrometric Bias with Respect to Source Catalog

If one were to measure the equatorial (J2000) positions of sources off Atlas Images, e.g., via a flux-weighted centroid or peak-finding algorithm, there could be a systematic difference with the astrometrically calibrated positions from the WISE Source Catalog. The latter was calibrated with respect to 2MASS to an accuracy of <~ 0.4 arcsec over the sky (section VI.4). For reasons not yet understood, the absolute (radial) differences between Atlas Image-derived source peaks and "true" astrometric positions vary with location on the sky and are typically <~ 0.25 arcsec for bands 1 and 2, and <~ 1.2 arcsec for bands 3 and 4 (90th percentile upper limits). A procedure to correct the Atlas Image-derived source positions and/or image WCS in general (if significant biases exist) is given in section II.3.g.

iv. The intensity units of Atlas Image pixels are Digital Numbers (DN)

Pixel units in the Atlas Images (and single-exposure images) are not calibrated in terms of absolute surface brightness. Their units are digital numbers (DN). The images are designed for photometric measurements relative to a local background using the photometric Zero Point Magnitude (MAGZP) provided in their FITS headers. Section II.3.f describes how the Atlas Image DN values (and measurements derived therefrom in DN) can be converted to absolute flux units.

v. Background (frame-overlap) Matching

One of the first steps in the Atlas Image generation pipeline is background level matching of the single-exposure frames. Since WISE had no requirements for measuring the absolute intensity of the background, we adopted a simple, fast, locally self-consistent method. Only the single exposure frames touching an individual Atlas Image tile (independent of all those touching neighboring tiles) were matched with respect to each other. Two caveats of this method are:

  1. Background gradients and levels will not be continuous across Atlas tile boundaries on the sky. I.e., systematic "step-like" patterns will result if one attempts to stitch together several or more tiles across the sky.

  2. Within an individual tile, the method assumes the difference in levels in the overlap region between any pair of frames is spatially constant. This is usually a good approximation, however, it breaks down when the background gradient is not the same across frames in their overlap region (i.e., that "see" the same piece of sky). This usually occurs when the frames are contaminated by scattered moon-light and results in step-like patterns across frame boundaries in an Atlas Image.

vi. Atlas Image Artifacts

The Anomaly Gallery contains examples of the artifacts commonly encountered in Atlas Images. Overall, these fall in two broad categories, with much overlap between the two:

vii. Saturation

Saturated pixels are masked in the single exposure frames and omitted when constructing the Atlas Images. For bright regions and sources exceeding the saturation limits, pixels in the Atlas Image intensity and uncertainty maps will be associated with NaN (Not-a-Number) values. The corresponding depth-of-coverage map will have zero coverage in these regions. These "holes" are typically seen at the location of the peak-emission of sources. An example is shown here.

viii. Missed (Unmasked) Saturation

The automatic saturation tagging that occurred on board the WISE spacecraft worked rather well, however, there were times when it was not reliable. This occurred intermittently when the counts were at the highest end of the dynamic range in any band. Hence, there are instances in regions of very bright emission, including the cores of very bright sources where saturated frame pixels (with anomalous values) were included when constructing the Atlas Images. The values of these pixels are generally low relative to that expected for the region. An example is shown in Figure 1 and it is generally seen in all bands. Given that the single exposures were also affected and used for simultaneous PSF-fit photometry, the impact on the catalog photometry is described in section I.4.b.

ix. Over-tagging of Outliers in Complex Regions

In regions with complex emission or a fast spatially-varying background (e.g., parts of the galactic plane), pixels may be erroneously tagged as outliers across a stack of input frames by the pixel-outlier rejection step. This results in sporadic holes (NaNs) in the Atlas Images, particularly in bands W1 and W2 (e.g., Figure 1). This is caused by the large variance in the background levels within frame-overlap regions. For details, see the last paragraph in section IV.4.f.3. The number of tagged outliers is further inflated by the outlier-expansion step (intended for moving object mitigation) since this is triggered when the spatial density of outliers exceeds some threshold. One set of outlier detection/expansion parameters were used for the entire sky for each band. Given the heterogeneous nature of the survey, there's no guarantee this parameter set produced consistent results throughout.

Figure 1 - Atlas Image cutouts near the galactic center: bands W1, W2, W3, W4 - top left, top right, bottom left, and bottom right respectively. Magenta regions represent NaN'd (zero-coverage) regions. W1 shows an example of the outlier-overtagging anomaly (NaNs at otherwise genuine depressions in the emission); W3 and W4 show examples of the impact of including frame pixels which were not masked for saturation (dark depressions meshed with NaN'd regions properly masked for saturation).

x. Low-flux Banding Artifacts

In regions with very-bright emission, W3 and W4 Atlas Images often show banding patterns with depressed flux. The regions need not be saturated or close to saturation. This effect is due to inadvertently unmasked pixel rows at the top and bottom edges of the input W3 and W4 single-exposure frames that have a relatively low responsivity. These low-response rows were not completely captured in the static flat-field calibration products to enable their removal since their responsivity was slightly transient. Given that the low-response pixel rows have a multiplicative effect on the signal that falls on them, higher signals will suffer a proportionally greater loss in their output counts. These anomalously low counts fall below the detector saturation thresholds and therefore remain unmasked. This banding effect is seen in the bright regions of the W3 and W4 Atlas Image-cutouts shown in Figures 1 and 2. Note that the flux along a "band" could be depressed by as much as 12% over the entire length of the band spanning an Atlas Image. Therefore, all sources or emission intercepting such bands are likely to have a biased flux.

Figure 2 - Atlas Image cutouts showing the core of the Orion Nebula, left: W3; right: W4. Magenta regions represent NaN'd (zero-coverage) regions due to saturation in all the input frames at that location. See section I.4.c.x. for details.

xi. Effective Size of a "point-source" in an Atlas Image

The effective size of the PSF in an Atlas Image is not the same as that inferred from the single-exposure frames. For the latter, the azimuthally-averaged FWHM of a point source profile is ≈ 5.8″, 6.4″, 6.7″, and 11.8″ for bands W1, W2, W3, and W4 respectively (e.g., see Table 1 in section IV.4.c.iii.1). For Atlas Image (co-adds) however, the FWHM of a point source profile is ≈ √2 times larger than the native (single-exposure) values, or ≈ 8.3″, 9.1″, 9.5″, and 16.8″ in W1, W2, W3, and W4 respectively (however, see caveat below). This additional smoothing arises from use of the native PSF as an interpolation kernel during the co-addition process (for details, see section IV.4.f.vii). This includes the small inevitable amount of smoothing from mapping onto a new grid with finite-sized pixels. The PSF-interpolation makes the Atlas Images also serve as match-filtered products optimized for detecting sources in the pipeline (for details, see section IV.4.b).

The Atlas Image PSF FWHMs quoted above are global ballpark measures and not representative of any one Atlas Image. A "highly-homogenised" set of Atlas Image PSFs is provided in section IV.4.c.viii. These were created from Atlas Images at high ecliptic latitudes where the high depth-of-coverage and large spread in single-exposure rotations acted to circularize the PSF. Owing to the asymmetric nature of the native PSFs (even after co-addition for low-to-moderate depths-of-coverage), we recommended you derive the PSF for your Atlas Image of interest. To obtain an accurate PSF, you may need to combine measurements from multiple Atlas Images with similar depths-of-coverage and input single-exposure geometries.

Last update: 2012 May 15

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