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<h2><span class="refentrytitle"><a name="libvips-convolution.top_of_page"></a>convolution</span></h2>
<p>convolution — convolve and correlate images</p>
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<div class="refsect1">
<a name="libvips-convolution.stability-level"></a><h2>Stability Level</h2>
Stable, unless otherwise indicated
</div>
<div class="refsynopsisdiv">
<a name="libvips-convolution.synopsis"></a><h2>Synopsis</h2>
<pre class="synopsis">
#include <vips/vips.h>
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-aconv" title="im_aconv ()">im_aconv</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>,
<em class="parameter"><code><span class="type">int</span> n_layers</code></em>,
<em class="parameter"><code><span class="type">int</span> cluster</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-aconvsep" title="im_aconvsep ()">im_aconvsep</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>,
<em class="parameter"><code><span class="type">int</span> n_layers</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-addgnoise" title="im_addgnoise ()">im_addgnoise</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">double</span> sigma</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-compass" title="im_compass ()">im_compass</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-contrast-surface" title="im_contrast_surface ()">im_contrast_surface</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">int</span> half_win_size</code></em>,
<em class="parameter"><code><span class="type">int</span> spacing</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()">im_conv</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-conv-f" title="im_conv_f ()">im_conv_f</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-convsep" title="im_convsep ()">im_convsep</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-convsep-f" title="im_convsep_f ()">im_convsep_f</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-fastcor" title="im_fastcor ()">im_fastcor</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-grad-x" title="im_grad_x ()">im_grad_x</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-grad-y" title="im_grad_y ()">im_grad_y</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-gradcor" title="im_gradcor ()">im_gradcor</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-gradient" title="im_gradient ()">im_gradient</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-lindetect" title="im_lindetect ()">im_lindetect</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-sharpen" title="im_sharpen ()">im_sharpen</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">int</span> mask_size</code></em>,
<em class="parameter"><code><span class="type">double</span> x1</code></em>,
<em class="parameter"><code><span class="type">double</span> y2</code></em>,
<em class="parameter"><code><span class="type">double</span> y3</code></em>,
<em class="parameter"><code><span class="type">double</span> m1</code></em>,
<em class="parameter"><code><span class="type">double</span> m2</code></em>);
<span class="returnvalue">int</span> <a class="link" href="libvips-convolution.html#im-spcor" title="im_spcor ()">im_spcor</a> (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);
</pre>
</div>
<div class="refsect1">
<a name="libvips-convolution.description"></a><h2>Description</h2>
<p>
These operations convolve an image in some way, or are operations based on
simple convolution, or are useful with convolution.
</p>
</div>
<div class="refsect1">
<a name="libvips-convolution.details"></a><h2>Details</h2>
<div class="refsect2">
<a name="im-aconv"></a><h3>im_aconv ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_aconv (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>,
<em class="parameter"><code><span class="type">int</span> n_layers</code></em>,
<em class="parameter"><code><span class="type">int</span> cluster</code></em>);</pre>
<p>
Perform an approximate convolution of <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em>.
</p>
<p>
The output image
always has the same <span class="type">VipsBandFmt</span> as the input image.
</p>
<p>
Larger values for <em class="parameter"><code>n_layers</code></em> give more accurate
results, but are slower. As <em class="parameter"><code>n_layers</code></em> approaches the mask radius, the
accuracy will become close to exact convolution and the speed will drop to
match. For many large masks, such as Gaussian, <em class="parameter"><code>n_layers</code></em> need be only 10% of
this value and accuracy will still be good.
</p>
<p>
Smaller values of <em class="parameter"><code>cluster</code></em> will give more accurate results, but be slower
and use more memory. 10% of the mask radius is a good rule of thumb.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-convsep-f" title="im_convsep_f ()"><code class="function">im_convsep_f()</code></a>, <a class="link" href="libvips-mask.html#im-create-dmaskv" title="im_create_dmaskv ()"><code class="function">im_create_dmaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>n_layers</code></em> :</span></p></td>
<td>number of layers for approximation</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>cluster</code></em> :</span></p></td>
<td>cluster lines closer than this distance</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-aconvsep"></a><h3>im_aconvsep ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_aconvsep (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>,
<em class="parameter"><code><span class="type">int</span> n_layers</code></em>);</pre>
<p>
Perform an approximate separable convolution of <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em>.
</p>
<p>
The mask must be 1xn or nx1 elements.
The output image
always has the same <span class="type">VipsBandFmt</span> as the input image.
</p>
<p>
The image is convolved twice: once with <em class="parameter"><code>mask</code></em> and then again with <em class="parameter"><code>mask</code></em>
rotated by 90 degrees.
</p>
<p>
Larger values for <em class="parameter"><code>n_layers</code></em> give more accurate
results, but are slower. As <em class="parameter"><code>n_layers</code></em> approaches the mask radius, the
accuracy will become close to exact convolution and the speed will drop to
match. For many large masks, such as Gaussian, <em class="parameter"><code>n_layers</code></em> need be only 10% of
this value and accuracy will still be good.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-convsep-f" title="im_convsep_f ()"><code class="function">im_convsep_f()</code></a>, <a class="link" href="libvips-mask.html#im-create-dmaskv" title="im_create_dmaskv ()"><code class="function">im_create_dmaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>n_layers</code></em> :</span></p></td>
<td>number of layers for approximation</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-addgnoise"></a><h3>im_addgnoise ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_addgnoise (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">double</span> sigma</code></em>);</pre>
<p>
Add gaussian noise with mean 0 and variance sigma to <em class="parameter"><code>in</code></em>.
The noise is generated by averaging 12 random numbers,
see page 78, PIETGEN, 1989.
</p>
<p>
See also: <a class="link" href="libvips-conversion.html#im-gaussnoise" title="im_gaussnoise ()"><code class="function">im_gaussnoise()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>sigma</code></em> :</span></p></td>
<td>standard deviation of noise</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-compass"></a><h3>im_compass ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_compass (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);</pre>
<p>
<em class="parameter"><code>in</code></em> is convolved 8 times with <em class="parameter"><code>mask</code></em>, each time <em class="parameter"><code>mask</code></em> is rotated by 45
degrees. Each output pixel is the largest absolute value of the 8
convolutions.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-lindetect" title="im_lindetect ()"><code class="function">im_lindetect()</code></a>, <a class="link" href="libvips-convolution.html#im-gradient" title="im_gradient ()"><code class="function">im_gradient()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-contrast-surface"></a><h3>im_contrast_surface ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_contrast_surface (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">int</span> half_win_size</code></em>,
<em class="parameter"><code><span class="type">int</span> spacing</code></em>);</pre>
<p>
Generate an image where the value of each pixel represents the
contrast within a window of half_win_size from the corresponsing
point in the input image. Sub-sample by a factor of spacing.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-spcor" title="im_spcor ()"><code class="function">im_spcor()</code></a>, <a class="link" href="libvips-convolution.html#im-gradcor" title="im_gradcor ()"><code class="function">im_gradcor()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>half_win_size</code></em> :</span></p></td>
<td>window radius</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>spacing</code></em> :</span></p></td>
<td>subsample output by this</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error.</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-conv"></a><h3>im_conv ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_conv (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);</pre>
<p>
Convolve <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em> using integer arithmetic. The output image
always has the same <span class="type">VipsBandFmt</span> as the input image.
</p>
<p>
Each output pixel is
calculated as sigma[i]{pixel[i] * mask[i]} / scale + offset, where scale
and offset are part of <em class="parameter"><code>mask</code></em>. For integer <em class="parameter"><code>in</code></em>, the division by scale
includes round-to-nearest.
</p>
<p>
Convolutions on unsigned 8-bit images are calculated with the
processor's vector unit,
if possible. Disable this with --vips-novector or IM_NOVECTOR.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-conv-f" title="im_conv_f ()"><code class="function">im_conv_f()</code></a>, <a class="link" href="libvips-convolution.html#im-convsep" title="im_convsep ()"><code class="function">im_convsep()</code></a>, <a class="link" href="libvips-mask.html#im-create-imaskv" title="im_create_imaskv ()"><code class="function">im_create_imaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-conv-f"></a><h3>im_conv_f ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_conv_f (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>);</pre>
<p>
Convolve <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em> using floating-point arithmetic. The output image
is always <code class="literal">IM_BANDFMT_FLOAT</code> unless <em class="parameter"><code>in</code></em> is <code class="literal">IM_BANDFMT_DOUBLE</code>, in which case
<em class="parameter"><code>out</code></em> is also <code class="literal">IM_BANDFMT_DOUBLE</code>.
</p>
<p>
Each output pixel is
calculated as sigma[i]{pixel[i] * mask[i]} / scale + offset, where scale
and offset are part of <em class="parameter"><code>mask</code></em>.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>, <a class="link" href="libvips-convolution.html#im-convsep-f" title="im_convsep_f ()"><code class="function">im_convsep_f()</code></a>, <a class="link" href="libvips-mask.html#im-create-dmaskv" title="im_create_dmaskv ()"><code class="function">im_create_dmaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-convsep"></a><h3>im_convsep ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_convsep (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);</pre>
<p>
Perform a separable convolution of <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em> using integer arithmetic.
See <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a> for a detailed description.
</p>
<p>
The mask must be 1xn or nx1 elements.
The output image
always has the same <span class="type">VipsBandFmt</span> as the input image.
</p>
<p>
The image is convolved twice: once with <em class="parameter"><code>mask</code></em> and then again with <em class="parameter"><code>mask</code></em>
rotated by 90 degrees. This is much faster for certain types of mask
(gaussian blur, for example) than doing a full 2D convolution.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-convsep-f" title="im_convsep_f ()"><code class="function">im_convsep_f()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>, <a class="link" href="libvips-mask.html#im-create-imaskv" title="im_create_imaskv ()"><code class="function">im_create_imaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-convsep-f"></a><h3>im_convsep_f ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_convsep_f (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#DOUBLEMASK:CAPS" title="DOUBLEMASK"><span class="type">DOUBLEMASK</span></a> *mask</code></em>);</pre>
<p>
Perform a separable convolution of <em class="parameter"><code>in</code></em> with <em class="parameter"><code>mask</code></em> using floating-point
arithmetic.
</p>
<p>
The mask must be 1xn or nx1 elements.
The output image
is always <code class="literal">IM_BANDFMT_FLOAT</code> unless <em class="parameter"><code>in</code></em> is <code class="literal">IM_BANDFMT_DOUBLE</code>, in which case
<em class="parameter"><code>out</code></em> is also <code class="literal">IM_BANDFMT_DOUBLE</code>.
</p>
<p>
The image is convolved twice: once with <em class="parameter"><code>mask</code></em> and then again with <em class="parameter"><code>mask</code></em>
rotated by 90 degrees. This is much faster for certain types of mask
(gaussian blur, for example) than doing a full 2D convolution.
</p>
<p>
Each output pixel is
calculated as sigma[i]{pixel[i] * mask[i]} / scale + offset, where scale
and offset are part of <em class="parameter"><code>mask</code></em>.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-convsep" title="im_convsep ()"><code class="function">im_convsep()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>, <a class="link" href="libvips-mask.html#im-create-dmaskv" title="im_create_dmaskv ()"><code class="function">im_create_dmaskv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-fastcor"></a><h3>im_fastcor ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_fastcor (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);</pre>
<p>
Calculate a fast correlation surface.
</p>
<p>
<em class="parameter"><code>ref</code></em> is placed at every position in <em class="parameter"><code>in</code></em> and the sum of squares of
differences calculated. One-band, 8-bit unsigned images only. The output
image is always <code class="literal">IM_BANDFMT_UINT</code>. <em class="parameter"><code>ref</code></em> must be smaller than or equal to
<em class="parameter"><code>in</code></em>. The output
image is the same size as the input.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-spcor" title="im_spcor ()"><code class="function">im_spcor()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>ref</code></em> :</span></p></td>
<td>reference image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-grad-x"></a><h3>im_grad_x ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_grad_x (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);</pre>
<p>
Find horizontal differences between adjacent pixels.
</p>
<p>
Generates an image where the value of each pixel is the difference between
it and the pixel to its right. The output has the same height as the input
and one pixel less width. One-band integer formats only. The result is
always <code class="literal">IM_BANDFMT_INT</code>.
</p>
<p>
This operation is much faster than (though equivalent to) <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a> with the
mask [[-1, 1]].
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-grad-y" title="im_grad_y ()"><code class="function">im_grad_y()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-grad-y"></a><h3>im_grad_y ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_grad_y (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);</pre>
<p>
Find vertical differences between adjacent pixels.
</p>
<p>
Generates an image where the value of each pixel is the difference between
it and the pixel below it. The output has the same width as the input
and one pixel less height. One-band integer formats only. The result is
always <code class="literal">IM_BANDFMT_INT</code>.
</p>
<p>
This operation is much faster than (though equivalent to) <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a> with the
mask [[-1], [1]].
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-grad-x" title="im_grad_x ()"><code class="function">im_grad_x()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-gradcor"></a><h3>im_gradcor ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_gradcor (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);</pre>
<p>
Calculate a correlation surface.
</p>
<p>
<em class="parameter"><code>ref</code></em> is placed at every position in <em class="parameter"><code>in</code></em> and a correlation coefficient
calculated. One-band, integer images only. <em class="parameter"><code>in</code></em> and <em class="parameter"><code>ref</code></em> must have the
same <span class="type">VipsBandFmt</span>. The output
image is always <code class="literal">IM_BANDFMT_FLOAT</code>. <em class="parameter"><code>ref</code></em> must be smaller than <em class="parameter"><code>in</code></em>. The output
image is the same size as the input.
</p>
<p>
The method takes the gradient images of the two images then takes the
dot-product correlation of the two vector images.
The vector expression of this method is my (tcv) own creation. It is
equivalent to the complex-number method of:
</p>
<p>
ARGYRIOU, V. et al. 2003. Estimation of sub-pixel motion using
gradient cross correlation. Electronics Letters, 39 (13).
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-spcor" title="im_spcor ()"><code class="function">im_spcor()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>ref</code></em> :</span></p></td>
<td>reference image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-gradient"></a><h3>im_gradient ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_gradient (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);</pre>
<p>
<em class="parameter"><code>in</code></em> is convolved with <em class="parameter"><code>mask</code></em> and with <em class="parameter"><code>mask</code></em> after a 90 degree rotation. The
result is the sum of the absolute value of the two convolutions.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-lindetect" title="im_lindetect ()"><code class="function">im_lindetect()</code></a>, <a class="link" href="libvips-convolution.html#im-gradient" title="im_gradient ()"><code class="function">im_gradient()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-lindetect"></a><h3>im_lindetect ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_lindetect (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><a class="link" href="libvips-mask.html#INTMASK:CAPS" title="INTMASK"><span class="type">INTMASK</span></a> *mask</code></em>);</pre>
<p>
<em class="parameter"><code>in</code></em> is convolved four times with <em class="parameter"><code>mask</code></em>, each time <em class="parameter"><code>mask</code></em> is rotated by 45
degrees. Each output pixel is the largest absolute value of the four
convolutions.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-compass" title="im_compass ()"><code class="function">im_compass()</code></a>, <a class="link" href="libvips-convolution.html#im-gradient" title="im_gradient ()"><code class="function">im_gradient()</code></a>, <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask</code></em> :</span></p></td>
<td>convolution mask</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-sharpen"></a><h3>im_sharpen ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_sharpen (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>,
<em class="parameter"><code><span class="type">int</span> mask_size</code></em>,
<em class="parameter"><code><span class="type">double</span> x1</code></em>,
<em class="parameter"><code><span class="type">double</span> y2</code></em>,
<em class="parameter"><code><span class="type">double</span> y3</code></em>,
<em class="parameter"><code><span class="type">double</span> m1</code></em>,
<em class="parameter"><code><span class="type">double</span> m2</code></em>);</pre>
<p>
Selectively sharpen the L channel of a LAB image. Works for <code class="literal">IM_CODING_LABQ</code>
and LABS images.
</p>
<p>
The operation performs a gaussian blur of size <em class="parameter"><code>mask_size</code></em> and subtracts
from <em class="parameter"><code>in</code></em> to
generate a high-frequency signal. This signal is passed through a lookup
table formed from the five parameters and added back to <em class="parameter"><code>in</code></em>.
</p>
<p>
The lookup table is formed like this:
</p>
<p>
</p>
<div class="informalexample"><pre class="programlisting">
^
y2 |- - - - - -----------
| /
| / slope m2
| .../
-x1 | ... |
-------------------...---------------------->
| ... | x1
|... slope m1
/ |
/ m2 |
/ |
/ |
/ |
/ |
______/ _ _ _ _ _ _ | -y3
|
</pre></div>
<p>
</p>
<p>
For printing, we recommend the following settings:
</p>
<p>
</p>
<div class="informalexample"><pre class="programlisting">
mask_size == 7
x1 == 1.5
y2 == 20 (don't brighten by more than 20 L*)
y3 == 50 (can darken by up to 50 L*)
m1 == 1 (some sharpening in flat areas)
m2 == 2 (more sharpening in jaggy areas)
</pre></div>
<p>
</p>
<p>
If you want more or less sharpening, we suggest you just change the m1
and m2 parameters.
</p>
<p>
The <em class="parameter"><code>mask_size</code></em> parameter changes the width of the fringe and can be
adjusted according to the output printing resolution. As an approximate
guideline, use 3 for 4 pixels/mm (CRT display resolution), 5 for 8
pixels/mm, 7 for 12 pixels/mm and 9 for 16 pixels/mm (300 dpi == 12
pixels/mm). These figures refer to the image raster, not the half-tone
resolution.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-conv" title="im_conv ()"><code class="function">im_conv()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>mask_size</code></em> :</span></p></td>
<td>how large a mask to use</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>x1</code></em> :</span></p></td>
<td>flat/jaggy threshold</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>y2</code></em> :</span></p></td>
<td>maximum amount of brightening</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>y3</code></em> :</span></p></td>
<td>maximum amount of darkening</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>m1</code></em> :</span></p></td>
<td>slope for flat areas</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>m2</code></em> :</span></p></td>
<td>slope for jaggy areas</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error.</td>
</tr>
</tbody>
</table></div>
</div>
<hr>
<div class="refsect2">
<a name="im-spcor"></a><h3>im_spcor ()</h3>
<pre class="programlisting"><span class="returnvalue">int</span> im_spcor (<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *in</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *ref</code></em>,
<em class="parameter"><code><a class="link" href="VipsImage.html" title="VipsImage"><span class="type">VipsImage</span></a> *out</code></em>);</pre>
<p>
Calculate a correlation surface.
</p>
<p>
<em class="parameter"><code>ref</code></em> is placed at every position in <em class="parameter"><code>in</code></em> and the correlation coefficient
calculated. One-band, 8 or 16-bit images only. <em class="parameter"><code>in</code></em> and <em class="parameter"><code>ref</code></em> must have the
same <span class="type">VipsBandFmt</span>. The output
image is always <code class="literal">IM_BANDFMT_FLOAT</code>. <em class="parameter"><code>ref</code></em> must be smaller than or equal to
<em class="parameter"><code>in</code></em>. The output
image is the same size as the input.
</p>
<p>
The correlation coefficient is calculated as:
</p>
<p>
</p>
<div class="informalexample"><pre class="programlisting">
sumij (ref(i,j)-mean(ref))(inkl(i,j)-mean(inkl))
c(k,l) = ------------------------------------------------
sqrt(sumij (ref(i,j)-mean(ref))^2) *
sqrt(sumij (inkl(i,j)-mean(inkl))^2)
</pre></div>
<p>
</p>
<p>
where inkl is the area of <em class="parameter"><code>in</code></em> centred at position (k,l).
</p>
<p>
from Niblack "An Introduction to Digital Image Processing",
Prentice/Hall, pp 138.
</p>
<p>
See also: <a class="link" href="libvips-convolution.html#im-gradcor" title="im_gradcor ()"><code class="function">im_gradcor()</code></a>, <a class="link" href="libvips-convolution.html#im-fastcor" title="im_fastcor ()"><code class="function">im_fastcor()</code></a>.
</p>
<div class="variablelist"><table border="0">
<col align="left" valign="top">
<tbody>
<tr>
<td><p><span class="term"><em class="parameter"><code>in</code></em> :</span></p></td>
<td>input image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>ref</code></em> :</span></p></td>
<td>reference image</td>
</tr>
<tr>
<td><p><span class="term"><em class="parameter"><code>out</code></em> :</span></p></td>
<td>output image</td>
</tr>
<tr>
<td><p><span class="term"><span class="emphasis"><em>Returns</em></span> :</span></p></td>
<td>0 on success, -1 on error</td>
</tr>
</tbody>
</table></div>
</div>
</div>
</div>
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