Depends On: Initial Settings; Mosaic Settings; Fiducial Image Frame; Med Filter
PURPOSE
This module performs single frame radhit rejection (§8.2.1). It is the simplest of the outlier detection schemes. Bright detections with small areas are classified as radhits. By default, single frame radhit rejection is already run during the Spitzer MIPS and IRAC BCD pipeline processing, so this module is rarely needed. The radhit pixels are flagged in the status masks provided with the BCD products. If DCE Status Mask List is specified in the Initial Setup module, this module does not need to run again if the masks are satisfactory.
INPUT
Segmentation Threshold: (float) The number of sigma above the mean to be used as the initial threshold used for cluster detection.
Detection Max Area: (int) The maximum number of pixels in a connected area (cluster) that could be classified as radhits.
Radhit Threshold: (float) In order to classify a cluster of pixels as a radhit, at least one of the pixels should be greater than this threshold in sigma. This parameter should be set much higher than the segmentation threshold value.
Output directory: The subdirectory of <output_dir> that you wish to use for the output files. Default is Dmask-mosaic.
COMMAND LINE INPUT
&DETECT_RADHIT
Segmentation_Threshold = 3,
Detection_Max_Area = 3,
Radhit_Threshold = 10,
&END
In Global Parameters:
DMASK_DIR = Dmask-mosaic
OUTPUT
New DCE Mask Files (*_dmask.fits): This module will produces mask images flagging detected radhits by setting Bit 9 (see the Instrument Handbooks, available from the website, for bit definitions).
DISCUSSION
The first and most basic method of outlier rejection is the single frame outlier detection that represents spatial filtering of input images. It is performed on the input images. In the automated MIPS and IRAC pipelines, this step is included in the standard BCD processing. It is designed to detect relatively bright and spatially small radhits. The algorithm is a variant of image segmentation, and is based on the idea that when a relatively low detection threshold is applied, for each bright point source a large number of pixels will be detected above the threshold. Bright detections with small areas are, therefore, classified as radhits. For more information on all of the outlier rejection schemes available in MOPEX, see §8.2.
NOTE: For Spitzer data, radhit is run as part of pipeline processing, so users should generally not need to run this again.
