Non-Linear Background Removal
In the near-infrared, the background "sky" emission has structure at all size scales, primarily due to upper atmospheric aerosol & hydroxyl emission (the so-called "airglow" emission; cf. Ramsey et al 1992, MNRAS, 259. 751). The OH emission is the dominant component to the J (1.3 l m) and H-band (1.7 l m) backgrounds, while thermal continuum emission comprises the bulk of the K (2.2 l m) background; consequently, the J and H images tend to have more background ‘structure’. At times of severe airglow incidence, the background can have relatively high frequency (tens of arcseconds) features that resemble extended sources (re: galaxies), thus triggering false positive extended source detection. However, for the most part, the background variation in a given image (size 8.5X16’) is smooth and can be modeled with a cubic polynomial. A third-order polynomial is a good compromise between functions that are too stiff (planar or 1st order polynomials) and those that are too yielding (e.g., spline waves). For extended sources, the primary objective of the 2MASS project is to find and characterize galaxies (and other extended objects) smaller than ~2’ in diameter. We therefore attempt to remove airglow features slightly larger than this size scale to minimize random and systematic photometric error from non-zero background structure. For the case in which the airglow frequency is higher than we can remove, the photometry (particularly at H band) is severely compromised and the quality of the data is downgraded accordingly.
The background removal process is applied separately to the J, H, & K coadd images (512 X 1024 pixels each). Given the "cross-scan" size of one coadd image, a cubic polynomial, ax3 + bx2 +cx + d, provides an effective model for smooth background variations larger than ~3. Moreover, the "inscan" size (1024") allows cubic fit to each half of the coadd (lower 512", upper 512"). In addition to fitting a cubic polynomial to each half of the coadd, we also apply a fit to the "central" 512X512 pixels in order to smoothly ‘join’ the boundaries of the two background solution fits. The final 512X1024-solution fit is generated from a weighted average of each 512X512-block solution.
The fitting procedure is first preceded by an image "clean" operation. Stars and catalogued galaxies are masked from the image. Very bright stars (K < 6) require more complicated masking, including removal of their bright reflection halo, diffraction spikes, horizontal streaks, glints and persistence ghosts. Finally, in order to minimize contamination from faint stars and objects that escaped the masking procedure, we median filter the coadd with an 8X8 pixel filter (thus, degrading the resolution of each pixel to 8" chunks). The fitting schematic is illustrated in Fig. 1 . The 512X1024 coadd is represented by a thick-lined rectangle. Cubic fits are applied to the lower half, 512 X [1:512] pixels, the upper half, 512 X [513:1024] pixels, and the central half, 512 X [257:768] pixels, where we have first resampled the data with an 8X8 median filter.
Using a least-squares technique, a cubic polynomial is then iteratively fit with 3s rejection to each line (of the 512X512 block, with 8X8 median filtering). The line solutions are then used for input to the next step, where we fit a cubic polynomial to each column, thus areal coupling the line and column background solutions. The three block solution images are combined with a (1/D r) weighting scheme. Here D r refers to the relative radial ("in-scan") difference between any two given block solutions from some reference point. There are three "in-scan" reference points: 256, 512 and 768. So for example, combining the lower and central blocks at some point, Y’, gives the respective weights [1 / (256-Y’)] and [1 / (512 – Y’)]. With this technique we are able to smoothly combine the three independent solutions per coadd image. Note however, the "boundary" solutions for the upper and lower blocks are better constrained near the center of the image due to the weighed addition of the central block solution image. Conversely, the background solutions are not as well determined at the upper, >900, and lower, <128, "in-scan" image extremes.
Representative performance of the background removal operation is shown in Fig. 2:J , Fig. 3:H , & Fig. 4:K . The image data comes from a fairly typical ‘photometric’ Northern Hemisphere night, although the "airglow" emission is to some extent severe during the period that this data was acquired (see H-band, Fig 3). The figures show the raw image coadd, resultant background solution and residual (background subtracted) image. The gray-scale stretch ranges from -2s to 5s of the mean background level. The J & K raw images (Fig 2, 4) reveal fairly low level (smooth, but non-linear) background variations, while the corresponding residual images show very little (if any) background structure. However, airglow emission is much more prevalent in the H-band (Fig 3), with size scales smaller than ~2-3’, as evident in the residual image. It is this residual structure in the background (with amplitude >10% of the mean background noise) that can induce systematics in the photometry, parameterization (e.g., azimuthal ellipse fitting), and reliability (reference Tchester airglow tome).
Figures
