=head1 NAME
Imager::Filters - Entire Image Filtering Operations
=head1 SYNOPSIS
use Imager;
$img = ...;
$img->filter(type=>'autolevels');
$img->filter(type=>'autolevels', lsat=>0.2);
$img->filter(type=>'turbnoise')
# and lots of others
load_plugin("dynfilt/dyntest.so")
or die "unable to load plugin\n";
$img->filter(type=>'lin_stretch', a=>35, b=>200);
unload_plugin("dynfilt/dyntest.so")
or die "unable to load plugin\n";
$out = $img->difference(other=>$other_img);
=head1 DESCRIPTION
Filters are operations that have similar calling interface.
=over
=item filter()
Parameters:
=over
=item *
type - the type of filter, see L</Types of Filters>.
=item *
many other possible parameters, see L</Types of Filters> below.
=back
Returns the invocant (C<$self>) on success, returns a false value on
failure. You can call C<< $self->errstr >> to determine the cause of
the failure.
$self->filter(type => $type, ...)
or die $self->errstr;
=back
=head2 Types of Filters
Here is a list of the filters that are always available in Imager.
This list can be obtained by running the C<filterlist.perl> script
that comes with the module source.
Filter Arguments Default value
autolevels lsat 0.1
usat 0.1
autolevels_skew lsat 0.1
usat 0.1
skew 0
bumpmap bump lightx lighty
elevation 0
st 2
bumpmap_complex bump
channel 0
tx 0
ty 0
Lx 0.2
Ly 0.4
Lz -1
cd 1.0
cs 40.0
n 1.3
Ia (0 0 0)
Il (255 255 255)
Is (255 255 255)
contrast intensity
conv coef
fountain xa ya xb yb
ftype linear
repeat none
combine none
super_sample none
ssample_param 4
segments(see below)
gaussian stddev
gradgen xo yo colors
dist 0
hardinvert
hardinvertall
mosaic size 20
noise amount 3
subtype 0
postlevels levels 10
radnoise xo 100
yo 100
ascale 17.0
rscale 0.02
turbnoise xo 0.0
yo 0.0
scale 10.0
unsharpmask stddev 2.0
scale 1.0
watermark wmark
pixdiff 10
tx 0
ty 0
All parameters must have some value but if a parameter has a default
value it may be omitted when calling the filter function.
Every one of these filters modifies the image in place.
If none of the filters here do what you need, the
L<Imager::Engines/transform()> or L<Imager::Engines/transform2()>
function may be useful.
=for stopwords
autolevels bumpmap bumpmap_complex conv gaussian hardinvert hardinvertall
radnoise turbnoise unsharpmask gradgen postlevels
A reference of the filters follows:
=over
=item autolevels
Scales the luminosity of the image so that the luminosity will cover
the possible range for the image. C<lsat> and C<usat> truncate the
range by the specified fraction at the top and bottom of the range
respectively.
# increase contrast, losing little detail
$img->filter(type=>"autolevels")
or die $img->errstr;
The method used here is typically called L<Histogram
Equalization|http://en.wikipedia.org/wiki/Histogram_equalization>.
=item autolevels_skew
Scales the value of each channel so that the values in the image will
cover the whole possible range for the channel. C<lsat> and C<usat>
truncate the range by the specified fraction at the top and bottom of
the range respectively.
# increase contrast per channel, losing little detail
$img->filter(type=>"autolevels_skew")
or die $img->errstr;
# increase contrast, losing 20% of highlight at top and bottom range
$img->filter(type=>"autolevels", lsat=>0.2, usat=>0.2)
or die $img->errstr;
This filter was the original C<autolevels> filter, but it's typically
useless due to the significant color skew it can produce.
=item bumpmap
uses the channel C<elevation> image C<bump> as a bump map on your
image, with the light at (C<lightx>, C<lightty>), with a shadow length
of C<st>.
$img->filter(type=>"bumpmap", bump=>$bumpmap_img,
lightx=>10, lighty=>10, st=>5)
or die $img->errstr;
=item bumpmap_complex
uses the channel C<channel> image C<bump> as a bump map on your image.
If C<< Lz < 0 >> the three L parameters are considered to be the
direction of the light. If C<< Lz > 0 >> the L parameters are
considered to be the light position. C<Ia> is the ambient color,
C<Il> is the light color, C<Is> is the color of specular highlights.
C<cd> is the diffuse coefficient and C<cs> is the specular
coefficient. C<n> is the shininess of the surface.
$img->filter(type=>"bumpmap_complex", bump=>$bumpmap_img)
or die $img->errstr;
=item contrast
scales each channel by C<intensity>. Values of C<intensity> < 1.0
will reduce the contrast.
# higher contrast
$img->filter(type=>"contrast", intensity=>1.3)
or die $img->errstr;
# lower contrast
$img->filter(type=>"contrast", intensity=>0.8)
or die $img->errstr;
=item conv
performs 2 1-dimensional convolutions on the image using the values
from C<coef>. C<coef> should be have an odd length and the sum of the
coefficients must be non-zero.
# sharper
$img->filter(type=>"conv", coef=>[-0.5, 2, -0.5 ])
or die $img->errstr;
# blur
$img->filter(type=>"conv", coef=>[ 1, 2, 1 ])
or die $img->errstr;
# error
$img->filter(type=>"conv", coef=>[ -0.5, 1, -0.5 ])
or die $img->errstr;
=item fountain
renders a fountain fill, similar to the gradient tool in most paint
software. The default fill is a linear fill from opaque black to
opaque white. The points C<A(Cxa, ya)> and C<B(xb, yb)> control the
way the fill is performed, depending on the C<ftype> parameter:
=for stopwords ramping
=over
=item C<linear>
the fill ramps from A through to B.
=item C<bilinear>
the fill ramps in both directions from A, where AB defines the length
of the gradient.
=item C<radial>
A is the center of a circle, and B is a point on it's circumference.
The fill ramps from the center out to the circumference.
=item C<radial_square>
A is the center of a square and B is the center of one of it's sides.
This can be used to rotate the square. The fill ramps out to the
edges of the square.
=item C<revolution>
A is the center of a circle and B is a point on its circumference. B
marks the 0 and 360 point on the circle, with the fill ramping
clockwise.
=item C<conical>
A is the center of a circle and B is a point on it's circumference. B
marks the 0 and point on the circle, with the fill ramping in both
directions to meet opposite.
=back
The C<repeat> option controls how the fill is repeated for some
C<ftype>s after it leaves the AB range:
=over
=item C<none>
no repeats, points outside of each range are treated as if they were
on the extreme end of that range.
=item C<sawtooth>
the fill simply repeats in the positive direction
=item C<triangle>
the fill repeats in reverse and then forward and so on, in the
positive direction
=item C<saw_both>
the fill repeats in both the positive and negative directions (only
meaningful for a linear fill).
=item C<tri_both>
as for triangle, but in the negative direction too (only meaningful
for a linear fill).
=back
By default the fill simply overwrites the whole image (unless you have
parts of the range 0 through 1 that aren't covered by a segment), if
any segments of your fill have any transparency, you can set the
I<combine> option to 'normal' to have the fill combined with the
existing pixels. See the description of I<combine> in L<Imager::Fill>.
If your fill has sharp edges, for example between steps if you use
repeat set to 'triangle', you may see some aliased or ragged edges.
You can enable super-sampling which will take extra samples within the
pixel in an attempt anti-alias the fill.
The possible values for the super_sample option are:
=over
=item none
no super-sampling is done
=item grid
a square grid of points are sampled. The number of points sampled is
the square of ceil(0.5 + sqrt(ssample_param)).
=item random
a random set of points within the pixel are sampled. This looks
pretty bad for low ssample_param values.
=item circle
the points on the radius of a circle within the pixel are sampled.
This seems to produce the best results, but is fairly slow (for now).
=back
You can control the level of sampling by setting the ssample_param
option. This is roughly the number of points sampled, but depends on
the type of sampling.
The segments option is an arrayref of segments. You really should use
the L<Imager::Fountain> class to build your fountain fill. Each
segment is an array ref containing:
=over
=item start
a floating point number between 0 and 1, the start of the range of
fill parameters covered by this segment.
=item middle
a floating point number between start and end which can be used to
push the color range towards one end of the segment.
=item end
a floating point number between 0 and 1, the end of the range of fill
parameters covered by this segment. This should be greater than
start.
=item c0
=item c1
The colors at each end of the segment. These can be either
Imager::Color or Imager::Color::Float objects.
=item segment type
The type of segment, this controls the way the fill parameter varies
over the segment. 0 for linear, 1 for curved (unimplemented), 2 for
sine, 3 for sphere increasing, 4 for sphere decreasing.
=item color type
The way the color varies within the segment, 0 for simple RGB, 1 for
hue increasing and 2 for hue decreasing.
=back
Don't forget to use Imager::Fountain instead of building your own.
Really. It even loads GIMP gradient files.
# build the gradient the hard way - linear from black to white,
# then back again
my @simple =
(
[ 0, 0.25, 0.5, 'black', 'white', 0, 0 ],
[ 0.5. 0.75, 1.0, 'white', 'black', 0, 0 ],
);
# across
my $linear = $img->copy;
$linear->filter(type => "fountain",
ftype => 'linear',
repeat => 'sawtooth',
segments => \@simple,
xa => 0,
ya => $linear->getheight / 2,
xb => $linear->getwidth - 1,
yb => $linear->getheight / 2)
or die $linear->errstr;
# around
my $revolution = $img->copy;
$revolution->filter(type => "fountain",
ftype => 'revolution',
segments => \@simple,
xa => $revolution->getwidth / 2,
ya => $revolution->getheight / 2,
xb => $revolution->getwidth / 2,
yb => 0)
or die $revolution->errstr;
# out from the middle
my $radial = $img->copy;
$radial->filter(type => "fountain",
ftype => 'radial',
segments => \@simple,
xa => $im->getwidth / 2,
ya => $im->getheight / 2,
xb => $im->getwidth / 2,
yb => 0)
or die $radial->errstr;
=for stopwords Gaussian
=item gaussian
performs a Gaussian blur of the image, using C<stddev> as the standard
deviation of the curve used to combine pixels, larger values give
bigger blurs. For a definition of Gaussian Blur, see:
http://www.maths.abdn.ac.uk/~igc/tch/mx4002/notes/node99.html
Values of C<stddev> around 0.5 provide a barely noticeable blur,
values around 5 provide a very strong blur.
# only slightly blurred
$img->filter(type=>"gaussian", stddev=>0.5)
or die $img->errstr;
# more strongly blurred
$img->filter(type=>"gaussian", stddev=>5)
or die $img->errstr;
=item gradgen
renders a gradient, with the given I<colors> at the corresponding
points (x,y) in C<xo> and C<yo>. You can specify the way distance is
measured for color blending by setting C<dist> to 0 for Euclidean, 1
for Euclidean squared, and 2 for Manhattan distance.
$img->filter(type="gradgen",
xo=>[ 10, 50, 10 ],
yo=>[ 10, 50, 50 ],
colors=>[ qw(red blue green) ]);
=item hardinvert
X<filters, hardinvert>X<hardinvert>
inverts the image, black to white, white to black. All color channels
are inverted, excluding the alpha channel if any.
$img->filter(type=>"hardinvert")
or die $img->errstr;
=item hardinvertall
X<filters, hardinvertall>X<hardinvertall>
inverts the image, black to white, white to black. All channels are
inverted, including the alpha channel if any.
$img->filter(type=>"hardinvertall")
or die $img->errstr;
=item mosaic
produces averaged tiles of the given C<size>.
$img->filter(type=>"mosaic", size=>5)
or die $img->errstr;
=item noise
adds noise of the given C<amount> to the image. If C<subtype> is
zero, the noise is even to each channel, otherwise noise is added to
each channel independently.
# monochrome noise
$img->filter(type=>"noise", amount=>20, subtype=>0)
or die $img->errstr;
# color noise
$img->filter(type=>"noise", amount=>20, subtype=>1)
or die $img->errstr;
=for stopwords Perlin
=item radnoise
renders radiant Perlin turbulent noise. The center of the noise is at
(C<xo>, C<yo>), C<ascale> controls the angular scale of the noise ,
and C<rscale> the radial scale, higher numbers give more detail.
$img->filter(type=>"radnoise", xo=>50, yo=>50,
ascale=>1, rscale=>0.02)
or die $img->errstr;
=item postlevels
alters the image to have only C<levels> distinct level in each
channel.
$img->filter(type=>"postlevels", levels=>10)
or die $img->errstr;
=item turbnoise
renders Perlin turbulent noise. (C<xo>, C<yo>) controls the origin of
the noise, and C<scale> the scale of the noise, with lower numbers
giving more detail.
$img->filter(type=>"turbnoise", xo=>10, yo=>10, scale=>10)
or die $img->errstr;
=for stopwords unsharp
=item unsharpmask
performs an unsharp mask on the image. This increases the contrast of
edges in the image.
This is the result of subtracting a Gaussian blurred version of the
image from the original. C<stddev> controls the C<stddev> parameter
of the Gaussian blur. Each output pixel is:
in + scale * (in - blurred)
eg.
$img->filter(type=>"unsharpmask", stddev=>1, scale=>0.5)
or die $img->errstr;
C<unsharpmark> has the following parameters:
=for stopwords GIMP GIMP's
=over
=item *
C<stddev> - this is equivalent to the C<Radius> value in the GIMP's
unsharp mask filter. This controls the size of the contrast increase
around edges, larger values will remove fine detail. You should
probably experiment on the types of images you plan to work with.
Default: 2.0.
=item *
C<scale> - controls the strength of the edge enhancement, equivalent
to I<Amount> in the GIMP's unsharp mask filter. Default: 1.0.
=back
=item watermark
applies C<wmark> as a watermark on the image with strength C<pixdiff>,
with an origin at (C<tx>, C<ty>)
$img->filter(type=>"watermark", tx=>10, ty=>50,
wmark=>$wmark_image, pixdiff=>50)
or die $img->errstr;
=back
A demonstration of most of the filters can be found at:
http://www.develop-help.com/imager/filters.html
=head2 External Filters
As of Imager 0.48 you can create perl or XS based filters and hook
them into Imager's filter() method:
=over
=item register_filter()
Registers a filter so it is visible via Imager's filter() method.
Imager->register_filter(type => 'your_filter',
defaults => { parm1 => 'default1' },
callseq => [ qw/image parm1/ ],
callsub => \&your_filter);
$img->filter(type=>'your_filter', parm1 => 'something');
The following parameters are needed:
=over
=item *
C<type> - the type value that will be supplied to filter() to use your
filter.
=item *
C<defaults> - a hash of defaults for the filter's parameters
=item *
C<callseq> - a reference to an array of required parameter names.
=item *
C<callsub> - a code reference called to execute your filter. The
parameters passed to filter() are supplied as a list of parameter
name, value ... which can be assigned to a hash.
The special parameters C<image> and C<imager> are supplied as the low
level image object from $self and $self itself respectively.
The function you supply must modify the image in place.
To indicate an error, die with an error message followed by a
newline. C<filter()> will store the error message as the C<errstr()>
for the invocant and return false to indicate failure.
sub my_filter {
my %opts = @_;
_is_valid($opts{myparam})
or die "myparam invalid!\n";
# actually do the filtering...
}
=back
See L<Imager::Filter::Mandelbrot> for an example.
=back
=for stopwords DSOs
=head2 Plug-ins
The plug in interface is deprecated. Please use the Imager API, see
L<Imager::API> and L</External Filters> for details
It is possible to add filters to the module without recompiling Imager
itself. This is done by using DSOs (Dynamic shared object) available
on most systems. This way you can maintain your own filters and not
have to have it added to Imager, or worse patch every new version of
Imager. Modules can be loaded AND UNLOADED at run time. This means
that you can have a server/daemon thingy that can do something like:
load_plugin("dynfilt/dyntest.so")
or die "unable to load plugin\n";
$img->filter(type=>'lin_stretch', a=>35, b=>200);
unload_plugin("dynfilt/dyntest.so")
or die "unable to load plugin\n";
Someone decides that the filter is not working as it should -
F<dyntest.c> can be modified and recompiled, and then reloaded:
load_plugin("dynfilt/dyntest.so")
or die "unable to load plugin\n";
$img->filter(%hsh);
=for stopwords Linux Solaris HPUX OpenBSD FreeBSD TRU64 OSF1 AIX Win32 OS X
Note: This has been tested successfully on the following systems:
Linux, Solaris, HPUX, OpenBSD, FreeBSD, TRU64/OSF1, AIX, Win32, OS X.
=over
=item load_plugin()
This is a function, not a method, exported by default. You should
import this function explicitly for future compatibility if you need
it.
Accepts a single parameter, the name of a shared library file to load.
Returns true on success. Check Imager->errstr on failure.
=item unload_plugin()
This is a function, not a method, which is exported by default. You
should import this function explicitly for future compatibility if you
need it.
Accepts a single parameter, the name of a shared library to unload.
This library must have been previously loaded by load_plugin().
Returns true on success. Check Imager->errstr on failure.
=back
A few example plug-ins are included and built (but not installed):
=over
=item *
F<plugins/dyntest.c> - provides the C<null> (no action) filter, and
C<lin_stretch> filters. C<lin_stretch> stretches sample values
between C<a> and C<b> out to the full sample range.
=item *
F<plugins/dt2.c> - provides the C<html_art> filter that writes the
image to the HTML fragment file supplied in C<fname> as a HTML table.
=item *
F<plugins/flines.c> - provides the C<flines> filter that dims
alternate lines to emulate an old CRT display.
L<Imager::Filter::Flines> provides the same functionality.
=item *
F<plugins/mandelbrot.c> - provides the C<mandelbrot> filter that
renders the Mandelbrot set within the given range of x [-2, 0.5) and y
[-1.25, 1,25). L<Imager::Filter::Mandelbrot> provides a more flexible
Mandelbrot set renderer.
=back
=head2 Image Difference
=over
=item difference()
You can create a new image that is the difference between 2 other images.
my $diff = $img->difference(other=>$other_img);
For each pixel in $img that is different to the pixel in $other_img,
the pixel from $other_img is given, otherwise the pixel is transparent
black.
This can be used for debugging image differences ("Where are they
different?"), and for optimizing animated GIFs.
Note that $img and $other_img must have the same number of channels.
The width and height of $diff will be the minimum of each of the width
and height of $img and $other_img.
Parameters:
=over
=item *
C<other> - the other image object to compare against
=item *
C<mindist> - the difference between corresponding samples must be
greater than C<mindist> for the pixel to be considered different. So
a value of zero returns all different pixels, not all pixels. Range:
0 to 255 inclusive. Default: 0.
For large sample images this is scaled down to the range 0 .. 1.
=back
=back
=head1 AUTHOR
Arnar M. Hrafnkelsson, Tony Cook <tonyc@cpan.org>.
=head1 SEE ALSO
Imager, Imager::Filter::Flines, Imager::Filter::Mandelbrot
=head1 REVISION
$Revision$
=cut