File: deghosting_mask.pod

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=encoding utf8

=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

=back

=head1 AUTHORS

Lukáš Jirkovský