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=head1 NAME
deghosting_mask - Creates mask for removing ghosting in images
=head1 SYNOPSIS
B<deghosting_mask> [options] I<<image1>> I<<image2>> I<...>
=head1 DESCRIPTION
Takes a series of aligned photos, usually three or more, and generates masks
for removal of ghosts - Data that only appears in a minority of photos.
=head1 OPTIONS
=over
=item B<-o|--output> <path>
Prefix for output masks
=item B<-s|--sigma> <float>
Standard deviation of Gaussian weighting function (SIGMA > 0); default: 30
=item B<-i|--iterations> <int>
Number of iterations, default is (ITER > 0) default: 4
=item B<-t|--threshold> <float>
Threshold; default: 150
=item B<-c|--contrast> <float>
Change constrast before applying threshold; default: 1.3
=item B<-a|--advanced> <f|g|m|t|w>
Advanced settings. Possible options are:
=over
=item B<f> Use gray images for computation. It's about two times faster but it
usually returns worse results. You also have to change threshold to smaller
value (around 100)
=item B<g> Use gamma 2.2 correction instead of logarithm if input images are HDR
=item B<m> Do not scale image, NOTE: slows down process
=item B<t> Use simple threshold, may result in holes in images
=item B<w> Compute "complete" weights, not only probabilities
=back
=item B<-w|--save> <i|w>
Advanced save settings
=over
=item B<i> Save initial weigths
=item B<w> Save generated weigths
=back
=item B<-b> <int>
Image cache BLOCKSIZE in kilobytes; default: 2048KB
=item B<-m> <int>
Set image CACHESIZE in megabytes; default: 1024MB
=item B<-h|--help>
Display this help
=item B<-v|--verbose> <0|1>
Verbose, repeat for more verbose output
=head1 AUTHORS
Lukáš Jirkovský
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