Depends On: Detect; Mosaic Projection; Mosaic Dual Outlier
PURPOSE
This module is the last step in Dual Outlier detection. This module makes the correction to the dual outlier maps produced in the Mosaic Dual Outlier module. The dual detection map is processed in order to eliminate detection of the outskirts of legitimate point sources as dual outliers. If a dual outlier belongs to a cluster where the majority of pixels are not dual outliers, the chances are the pixel has been wrongly marked because it is on the edge of the point source.
INPUT
Threshold Ratio: (float) The threshold at which the sign of pixels within a cluster should be flipped (see below).
COMMAND LINE INPUT
&LEVEL
THRESHOLD_RATIO = 0.5,
&END
OUTPUT
Level Images (proj*_detmap_dual_outlier_level.fits): The stack of dual outlier rejection maps with all pixels within each detected cluster set to the same sign.
DISCUSSION
This step is the last of the Dual Outlier detection (see §8.2.3). The dual outlier detection represents a complicated dual spatial-temporal filtering. First, all spatial pixel outliers are detected and saved as detection maps. These detection maps include point sources and radhits. Detection maps are interpolated to a common grid. Then for each pixel position in the interpolated grid the values of the interpolated pixels in the detection maps are compared. If in the majority of the detection maps a given pixel location has not been detected by spatial filtering, then the detections are declared outliers. This method detects both moving objects and radhits. This method is expected to be reliable in the shallow coverage case.
The dual detection map is processed in order to eliminate detection of the outskirts of legitimate point sources as dual outliers. If a dual outlier belongs to a cluster where the majority of pixels are not dual outliers the chances are the pixel has been wrongly marked because it is on the edge of the point source. The sign of wrongly marked pixels is flipped based on the namelist parameter Threshold Ratio. The following is done:
if the number of negative pixels N- in a cluster with N pixels is smaller than the threshold
N- / N < Threshold Ratio,
then their signs are flipped. If the number of positive pixels N+ in a cluster with N pixels is smaller than the threshold
N+ / N < Threshold Ratio,
then their signs are flipped. If Threshold Ratio = 0.5, which is the default, the sign of pixels within each cluster will be determined by the majority of the pixels. The products of this step are the corrected dual detection maps.
