MOPEX User's Guide - IRSA

MOPEX User’s Guide
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:
biased _ median(I[k]) = I[N /2 − Bias]
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 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
Mosaicking (mosaic.pl) 77
Mosaic Modules