NAME

       mViewer - Render multi-dimensional images and large-scale images

DESCRIPTION

       mViewer  generates  a  JPEG  image file from a FITS file (or a set of three FITS files in full color).  A
       data range for each image can be defined, and the data can  be  stretched  by  any  power  of  the  log()
       function  (including  zero:  linear) or using custom gaussian histogram equalization algorithms.  Pseudo-
       color color tables can be applied in single-image mode.

       mViewer can also generate overlays on the  image  of  coordinate  grids,  source  catalogs  (with  scaled
       symbols), image outlings from metadata tables, plus various markers and labels.

       Along with a few other Montage modules, mViewer can be wrapped to support interactive image analysis from
       Python or through AJAX web interfaces.

       The functionality of mViewer goes beyond what is reasonable to capture  in  a  man  page.   The  user  is
       therefore directed to the mViewer documentation suite.

       Examples:

       To create a grayscale image from a FITS file:

       To create a full color image from three co-registered FITS files:

       A  complex  example  with  a  catalog overlay (symbol size, shape and color controlled by table columns),
       image metadata, a coordinate grid and some custom labeling:

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.