Important Notes:Using this module does not mean that MOPEX will automatically use the results for outlier detection. In order to use the results from this module, you must set Use Box Outlier For Rmask in the Mosaic RMask module and set the RMask Fatal Mask Bit Pattern in the Initial Setup module to use bit 3. Note that this is not the same as setting it to a value of 3. See §8.11: Fatal Mask Bit Patterns for more information.
PURPOSE
This module uses the Box Outlier rejection method to flag bad pixels (see §8.2.4). The method is designed to use both the temporal and spatial information like the Dual Outlier, but it uses the statistical analysis of the kind used by Multiframe Temporal Outlier. In the identification of temporal outliers, neighboring pixels are utilized to ensure the correct classification.
INPUT
Box Size X(Y) direction: (int) The X (Y) size of the box of neighboring pixels used for outlier detections.
Box Median Bias: (float) The computation of the mean and sigma for each pixel stack is done using a biased median. If there are N pixels in the stack, then the biased median is equal to the N/2 - Bias element of the stack:
Equation 5.4
Tile X(Y) Size: (int) Set these to smaller numbers to avoid memory problems with dealing with a large mosaic. See the discussion of Tiling for details (§8.1).
Box OutLier output subdirectory: The subdirectory of <output_dir> that you wish to use for the output files. Default is BoxOutlier-mosaic.
COMMAND LINE INPUT
&MOSAICBOXOUTLIERIN
BOX_X = 3,
BOX_Y = 3,
BOX_MEDIAN_BIAS = 1,
TILE_XSIZ = 500,
TILE_YSIZ = 500,
&END
In Global Parameters:
BOX_OUTLIER_DIR = BoxOutlier-mosaic
OUTPUT
Box Outlier Output FITS (interp_*_box_outlier.fits): The product of this step is an outlier map. The pixel value is the deviation of the pixel in the input image from the mean of that pixel in the stack, in terms of the number of sigma.
DISCUSSION
This module represents a more complicated dual spatial-temporal filtering (see §8.2.4). It extends the regular temporal outlier detection, which computes the statistics of the pixels in the stack for each mosaic pixel position, by including the pixels in the box region around that pixel in the statistics. This allows for detecting outliers even in the coverage = 2 case and, at the same time, provides a guard against detecting pixels inside bright point sources as outliers.
