NAME

       mBgModel - Re-project and mosaic your images, with background rectification

SYNOPSIS

       mBgModel  [-i  niter]  [-l(evel-only)]  [-d  level]  [-r  refimg]  [-s  statusfile]  images.tbl  fits.tbl
       corrections.tbl

DESCRIPTION

       mBgModel is a modelling/fitting program.  It uses the image-to-image difference parameter  table  created
       by  mFitExec to interactively determine a set of corrections to apply to each image in order to achieve a
       "best" global fit.

OPTIONS

       -i -niter
              Number of iterations (without switch, defaults to 5000). Can be between 1 and 32767.

       -l     Calculate level adjustments only (ie, don't attempt to match the slopes)

       -d level
              Turns on debugging to the specified level (1-3).

       -r refimg
              Turns on additional debugging for the nth image in images.tbl.

       -a     Use all the input differences (by default we exclude very small overlap areas).

       -s statusfile
              mBgModel output and errors are written to statusfile instead of to stdout.

ARGUMENTS

       images.tbl
              Image metadata table generated by mImgtbl.

       fits.tbl
              Plane fitting table generated by mFitExec.

       corrections.tbl
              Output table of background corrections

RESULT

       Output table containing corrections to be applied to each image.

MESSAGES

       OK     [struct stat="OK"]

       ERROR  Argument for -i (string) cannot be interpreted as an integer

       ERROR  Number of iterations too small (niter). This parameter is normally around 5000.

       ERROR  Argument for -r (string) cannot be interpreted as an integer

       ERROR  Cannot open status file: statusfile

       ERROR  Failed to open output filename

       ERROR  Invalid image metadata file: filename

       ERROR  Need columns: cntr nl ns crpix1 crpix2 in image info file

       ERROR  malloc() failed (ImgInfo)

       ERROR  realloc() failed (ImgInfo)

       ERROR  Invalid background fit parameters file: filename

       ERROR  Need columns: plus minus a b c crpix1 crpix2 xmin xmax ymin ymax xcenter ycenter npixel  rms  boxx
              boxy boxwidth boxheight boxang

       ERROR  malloc() failed (FitInfo)

       ERROR  realloc() failed (FitInfo)

       ERROR  malloc() failed (CorrInfo)

       ERROR  realloc() failed (CorrInfo)

       ERROR  Debug reference image out of range (0 - n)

       ERROR  Invalid fit type

       ERROR  Allocation failure in ivector()

EXAMPLES

       After  running mDiffExec to create a set of difference images in diffdir, we generate an image difference
       table using mFitExec: sample fits.tbl.

       $ mBgModel images.tbl fits.tbl corrections.tbl
              [struct stat="OK"]

       This results in the creation of corrections.tbl.

BUGS

       The drizzle algorithm has been implemented but has not been tested in this release.

       If a header template contains carriage returns (i.e., created/modified on a Windows machine), the cfitsio
       library  will  be  unable  to read it properly, resulting in the error: [struct stat="ERROR", status=207,
       msg="illegal character in keyword"]

       It is best for the background correction  algorithms  if  the  area  described  in  the  header  template
       completely encloses all of the input images in their entirety. If parts of input images are "chopped off"
       by the header template, the background correction will be affected. We  recommend  you  use  an  expanded
       header  for  the  reprojection  and background modeling steps, returning to the originally desired header
       size for the final coaddition. The default background matching  assumes  that  there  are  no  non-linear
       background  variations  in  the individual images (and therefore in the overlap differences). If there is
       any uncertainty in this regard, it is safer to turn on the "level only"  background  matching  (the  "-l"
       flag in mBgModel.

COPYRIGHT

       2001-2015 California Institute of Technology, Pasadena, California

       If  your  research uses Montage, please include the following acknowledgement: "This research made use of
       Montage. It is funded by the  National  Science  Foundation  under  Grant  Number  ACI-1440620,  and  was
       previously funded by the National Aeronautics and Space Administration's Earth Science Technology Office,
       Computation Technologies Project, under Cooperative  Agreement  Number  NCC5-626  between  NASA  and  the
       California Institute of Technology."

       The  Montage  distribution includes an adaptation of the MOPEX algorithm developed at the Spitzer Science
       Center.