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.

       -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.