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 controled 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.

Montage 3.3                                         June 2010                                         MVIEWER(1)