Point sources are detected in each instrumentally-corrected R1 and R2-R1 frame by identifying local intensity maxima. Positions are measured for these detections using a maximum-likelihood estimator, and magnitudes are estimated using aperture photometry within a 4´´ (two camera pixel) radius aperture.
The values for all the pixels are histogrammed, and the median sky value and the noise are estimated. The noise is estimated as one-half the distance between the 0.1587 and 0.8413 percentile points.
All the pixels in the frame are examined to identify local maxima. For each local maximum exceeding the local background by more than Tpk (where Tpk=4), the following computations are performed:
The centroid of the 3×3 pixel patch centered on the local maximum is first evaluated:
The local centroid is used as the initial source position, which is
then refined using the following maximum likelihood position estimation
technique, with the cost function on each axis computed by:
P = the normalized point spread function (PSF) and Ft
is the template amplitude,
Cx and Cy are followed to their zero crossings, and then interpolated to solve for (xc,yc).
The fraction of flux in the peak pixel (fpeak) is computed
The aperture photometry module is called to compute the aperture magnitude at the estimated position. The aperture photometry on a frame is performed by summing pixels entirely within the aperture and interpolating pixels partially within the aperture. The sky background for each object is computed in an annulus with an inner radius of 24.0´´ and an outer radius of 30.0´´. Pixels in the sky annulus are entirely included or excluded based on the distance of their centers from the source. The sky value is estimated by first excluding saturated, masked, or unreasonably low pixels. A -trimmed median of the surviving sky pixels is then used as the sky estimate. Aperture photometry and positions from the maximum six possible overlapping frames are later combined using an unweighted average for the R1 data.
The 3×3 pixel patch centered on the peak pixel along with the coordinates of the peak pixel and the aperture magnitude and associated error are written to a temporary file so that the detection parameters may be re-estimated in a second pass using a PSF matched to the seeing.
i. Bright Source (READ1) Aperture Photometry
The photometric dynamic range of 2MASS is extended by the use of the 51 ms R1 exposures. Sources saturate on the 1.3 sec R2-R1 exposures at magnitude levels of approximately 8.0, 7.5 and 7.0 at J, H, and Ks, respectively. For objects that are found to have one or more saturated pixels within the measurement aperture on the R2-R1 frames, the "default magnitude" quoted in the Point Source Catalog records is taken from the aperture photometry from the R1 frames. This is indicated by a value of "1" in the "rd_flg" parameter in the point source records, for the appropriate bands. Positions measured from the R1 frames are used in the final source position estimation only if R2-R1 profile fit results are not available.
The aperture photometry measured in this step for non-saturated R2-R1 sources from individual frames is not carried forward as part of the final source characteristics.
ii. Faint Source Detection
The fainter, and thus majority of sources found by 2MASS are detected from the Atlas Images. Each Atlas Image is convolved with a zero-sum 4´´ FWHM Gaussian over a 13-pixel sub-array. The resulting zero-sum filtered image is thresholded, and for each maximum over threshold, a detection is identified and a rough position estimate is computed from the corrected centroid. This detection process is in all essential aspects identical to that used in the FIND subprocess of the DAOPHOT II program developed by Peter Stetson (P.B. Stetson 1991). The detections list is sent to the software module that computes the running estimate of the seeing during a scan, and to the photometry routines that compute the refined estimates of flux and position. The detection threshold used is 3.0 times the estimated noise level for the Atlas Image. The noise level is estimated as the difference between the 50% and the 15.87% quantiles of the image histogram. This noise estimator has been found to be excessively sensitive to low frequency noise due to airglow (OH), and will be replaced by an estimate computed from the zero-sum filtered image for the final processing of the 2MASS data.
[Last Updated: 2000 June 20; by R. Cutri & E. Kopan]