Global and local variations in the depth-of-coverage are expected from the nominal survey design (section I.2.a.). 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.1.b.i. 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.
Examples of Atlas Images with low depth-of-coverage are shown in Figure 1. More examples are shown in the Atlas Image Anomaly Gallery for the All-Sky Data Release. Low coverage-depths are most prevalent in W3 and W4 since AllWISE multiframe processing for these bands only used frames from the 4-band cryo phase of the mission. Thus, the W3 and W4 AllWISE Atlas Image products are effectively equivalent to those in the All-Sky Data Release. The anomalies induced by low depth-of-coverage regions in the All-Sky Release also apply to the AllWISE Release for all bands.
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 AllWISE Source Catalog selection process explicitly excluded extractions from regions with a depth-of-coverage ≤ 4.
|Figure 1 - Example Atlas Images in W3 (left) and W4 (right) from tile ID 1799m076_ac51 showing the bleed-through of spurious artifacts in regions with low depth-of-coverage - in this case moving objects and cosmic rays. Corresponding depth maps are shown in Figure 2.|
|Figure 2 - Depth-of-coverage maps corresponding to the Atlas Images in Figure 1: W3 (left), W4 (right). Color-bar indicates the approximate depth.|
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 AllWISE Source Catalog. The latter has an accuracy of ~ 0.1″ (1-σ per axis) for high S/N sources over the sky (section II.5). For reasons not yet understood, the Atlas Image-derived source peak and "true" astrometric position differences vary with location on the sky and across bands. The 95th percentile upper limits in the radial differences are typically <~ 0.075″ in W1 and W2, <~ 0.43″ in W3, and <~ 1.1″ in W4. A procedure to correct the Atlas Image-derived source positions and/or image WCS in general (if significant biases exist) is given in section IV.3.b.
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 IV.3.a describes how photometric measurements on the Atlas Images in DN can be converted to absolute flux units.
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:
An anomaly seen in a handful of Atlas Images is the presence of non-astrophysical gradients in the background, in all bands. This is another caveat of the background frame-level matching algorithm (in addition to those in section IV.4.e. above). This is caused by the presence of bright sources falling on the first (seed) frame that sets the course for matching to all other frames falling in the co-add footprint (see algorithm for details). An example is shown in Figure 3.
|Figure 3 - Example of a W1 Atlas Image (tile ID 3107m379_ac51) with an unphysical background gradient induced by processing. The values on the color-bar are in DN.|
The Anomaly Gallery contains examples of the artifacts commonly encountered in Atlas Images. These examples are from the All-Sky Release Image Atlas and many of them carry over to AllWISE. Overall, these anomalies fall in two broad categories, with much overlap between the two:
It's also important to note that the AllWISE multiframe pipeline used reprocessed single-exposures from the 4-band cryo phase (all bands) and the 3-band cryo phase (W1 and W2 only), primarily to correct for an instrumental calibration issue as described in section V.2.a. Very little manual quality-assurance was performed on the regenerated single-exposures. The same frame quality scores from earlier frame-level QA (for the All-Sky and 3-band Data Releases) were used to determine frame usability for the AllWISE muiltiframe pipeline. As a consequence, some "badly" calibrated frames (not captured by the original quality scoring) still made it through to the muiltiframe pipeline. Their signature will also be most noticeable in Atlas Images with low depth-of-coverage regions. We expect this to be more prevalent in W3 and W4.
Saturated pixels were 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 that were bright enough to saturate on the detectors.
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. Despite workarounds to mitigate this effect (sections IV.4.j. and VII.3.b.), 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. Examples are shown in Figures 4 and 6 and is generally seen in all bands. Given that this also affected the single-exposures, their use in simultaneous PSF-fit photometry also impacted the bright source photometry as described in section II.2.c.
To mitigate the incidence of missed (unmasked) saturated pixels described above, a spatial-expansion algorithm was implemented to ensure more complete blanketing of the suspect saturated region. The amount of spatial expansion was rather conservative as to not severely impact source photometry. In general, this lead to more pixels being masked as saturated in and around the cores of sources in the AllWISE Atlas Images relative to those in the All-Sky release. An example is shown in Figure 4. The impact to the bright source photometry (relative to the All-Sky Release) is described in sections V.3.a.iii.4. and II.2.c.
|Figure 4 - W1 Atlas Image zoom-ins of Betelgeuse from the AllWISE Release (left) compared to the All-Sky Release (right). Magenta regions represent NaN'd (zero-coverage) regions due to saturation in all the input frames at that location. Despite the use of a "saturation-expansion" method for AllWISE (section IV.4.j.), there is still an unmasked periphery of pixels around the core.|
A related consequence of "saturation expansion" in general was noted when visually examining image cut-outs of 80 relatively bright motion-candidate stars during AllWISE Quality Assurance. These appeared to have a "mottled" or "pock-marked" appearance in the AllWISE Atlas Images, primarily in W1 and W2, that was not present in Atlas Images from the All-Sky Release. These stars were generally brighter than 6th-magnitude in W1 and hence well into the saturated regime. Figure 5 compares Atlas Image cut-outs from AllWISE and All-Sky, for a typical motion-candidate star exhibiting this phenomenon. The degraded visual appearance of this star in the AllWISE W1 and W2 tiles resulted from the inclusion during co-addition of relatively "warmer" single-exposures from the post-cryo phase of the mission that were more prone to saturation. The combination of "saturation expansion" (with greater masking of source cores), implicit smoothing during the coaddition and pixel-interpolation process, and temporal changes in the PSFs themselves all acted to change the overall morphology of bright sources on the AllWISE W1 and W2 Atlas Images. The impact on the photometry is discussed in section II.2.c.
|Figure 5 - Atlas Image zooms centered on a star with saturated cores in W1 and W2 from AllWISE tile 2700m319_ac51 (top row) and the equivalent from the All-Sky Release (bottom row).|
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 they were slightly transient. Given these 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 is seen in the bright regions of the W3 and W4 Atlas Image-cutouts shown in Figure 6. Note that the flux along a "band" could be depressed by as much as 12% over the entire length of an Atlas Image. Therefore, all sources or emission intercepting these bands are likely to have a biased flux.
|Figure 6 - W3 Atlas Image zoom-ins of the Galactic Center (left) and the core of the Orion Nebula (right). Magenta regions represent NaN'd (zero-coverage) regions due to saturation in all the input frames at that location.|
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: 20 November 2013