Improving the signal-to-noise of Mid-infra-red Data

The Michelle electronics can leave an uneven mosaic with vertical banding from bias variations and horizontal ripple patterns from electronic pickup. Therefore, Michelle NOD_CHOP recipes subtract the median along each column of the mosaic, then subtracts the median along each row. This cleaning aids the visibility of faint sources.

In the mid-infra-red, the sky signal is vastly greater than the signal than even the brightest sources. While the nodding removes the bulk of the sky signal, the sky noise remains, still swamping the signal from a faint source. Integrating over many nod-chop cycles is needed, and the real-time display of ORAC-DR does permit interactive review of the signal-to-noise in GAIA so observers can curtail data collection when the required contrast is achieved. Averaging the positive and negative signals and neighbourhoods into a combined signal (cf. mid-infra-red aperture photometry only helps by a factor of two (or $\sqrt{2}$ for a single positive and negative pair). Recipe NOD_CHOP_FAINT smooths the combined quadrant with a 4-by-4-pixel neighbourhood running average filter to help reveal faint sources. Note that the source centroids are not used for registration as the signal is usually too weak.

While smoothing reveals the sources, it is not sufficient. There is also a confusion issue. The chopping can bring positive and negative sources actually located beyond the final quadrant to within it. There is an option of the _COMBINE_CHOPPED_SOURCE_ primitive, called by recipe NOD_CHOP recipes, which attempts to clarify which sources are actually present in the quadrant by forming a quality map. Each quality pixel is the sum of the four corresponding pixel values divided by their absolute values, after changing sign for the quadrants containing the negative images. In the map +4 indicates that a pixel had positive contributions from the positive quadrants and negative signals from the negative quadrants. A quality of +4 strongly implies that the signal is really at the sky location indicated. Thus it helps to discriminate from sources which have been chopped into view, for which there are no positive or negative counterparts (values +/-2) or noise (0, +/-2). Around the sky (which should be near zero) noise randomises the quality measurement, therefore smoothing should be used in conjunction with the quality map.
[_COMBINE_CHOPPED_SOURCE_, _REMOVE_COLUMN_ROW_STRUCTURE_,
_REMOVE_COLUMN_ROW_STRUCTURE_SCAN_, FIND_SOURCE_CENTROID_,
_GET_CHOP_OFFSETS_, _GET_FRAME_CENTRE_]

To create a quality map at each cycle, you should set argument QMAP=1 and SMOOTH>1. For example in NOD_CHOP_FAINT, append " QMAP=1" to the line

      _COMBINE_CHOPPED_SOURCE_ METHOD=median CENTROID=0 SMOOTH=4 CLEAN=1