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<p class="navigation-index">[ <a href="#AdaptiveSharpenImage">AdaptiveSharpenImage</a> | <a href="#AdaptiveThresholdImage">AdaptiveThresholdImage</a> | <a href="#AddNoiseImage">AddNoiseImage</a> | <a href="#BilevelImage">BilevelImage</a> | <a href="#BlackThresholdImage">BlackThresholdImage</a> | <a href="#BlurImage">BlurImage</a> | <a href="#DespeckleImage">DespeckleImage</a> | <a href="#EdgeImage">EdgeImage</a> | <a href="#EmbossImage">EmbossImage</a> | <a href="#GaussianBlurImage">GaussianBlurImage</a> | <a href="#MedianFilterImage">MedianFilterImage</a> | <a href="#MotionBlurImage">MotionBlurImage</a> | <a href="#PreviewImage">PreviewImage</a> | <a href="#RadialBlurImage">RadialBlurImage</a> | <a href="#RandomThresholdImage">RandomThresholdImage</a> | <a href="#ReduceNoiseImage">ReduceNoiseImage</a> | <a href="#ShadeImage">ShadeImage</a> | <a href="#SharpenImage">SharpenImage</a> | <a href="#SpreadImage">SpreadImage</a> | <a href="#UnsharpMaskImage">UnsharpMaskImage</a> | <a href="#WhiteThresholdImage">WhiteThresholdImage</a> ]</p>

<div style="margin: auto;">
  <h2><a name="AdaptiveSharpenImage">AdaptiveSharpenImage</a></h2>
</div>

<p>AdaptiveSharpenImage() adaptively sharpens the image by sharpening more intensely near image edges and less intensely far from edges. We sharpen the image with a Gaussian operator of the given radius and standard deviation (sigma).  For reasonable results, radius should be larger than sigma.  Use a radius of 0 and AdaptiveSharpenImage() selects a suitable radius for you.</p>

<p>The format of the AdaptiveSharpenImage method is:</p>

<pre class="code">
  Image *AdaptiveSharpenImage(const Image *image,const double radius,
    const double sigma,ExceptionInfo *exception)
  Image *AdaptiveSharpenImageChannel(const Image *image,
    const ChannelType channel,double radius,const double sigma,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>radius</h4>
<p>The radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>sigma</h4>
<p>The standard deviation of the Laplacian, in pixels.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="AdaptiveThresholdImage">AdaptiveThresholdImage</a></h2>
</div>

<p>AdaptiveThresholdImage() selects an individual threshold for each pixel based on the range of intensity values in its local neighborhood.  This allows for thresholding of an image whose global intensity histogram doesn't contain distinctive peaks.</p>

<p>The format of the AdaptiveThresholdImage method is:</p>

<pre class="code">
  Image *AdaptiveThresholdImage(const Image *image,
    const unsigned long width,const unsigned long height,
    const long offset,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>width</h4>
<p>The width of the local neighborhood.</p>

<h4>height</h4>
<p>The height of the local neighborhood.</p>

<h4>offset</h4>
<p>The mean offset.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="AddNoiseImage">AddNoiseImage</a></h2>
</div>

<p>AddNoiseImage() adds random noise to the image.</p>

<p>The format of the AddNoiseImage method is:</p>

<pre class="code">
  Image *AddNoiseImage(const Image *image,const NoiseType noise_type,
    ExceptionInfo *exception)
  Image *AddNoiseImageChannel(const Image *image,const ChannelType channel,
    const NoiseType noise_type,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>noise_type</h4>
<p>The type of noise: Uniform, Gaussian, Multiplicative, Impulse, Laplacian, or Poisson.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="BilevelImage">BilevelImage</a></h2>
</div>

<p>BilevelImage() changes the value of individual pixels based on the intensity of each pixel channel.  The result is a high-contrast image.</p>

<p>The format of the BilevelImageChannel method is:</p>

<pre class="code">
  MagickBooleanType BilevelImage(Image *image,const double threshold)
  MagickBooleanType BilevelImageChannel(Image *image,
    const ChannelType channel,const double threshold)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>threshold</h4>
<p>define the threshold values.</p>

<div style="margin: auto;">
  <h2><a name="BlackThresholdImage">BlackThresholdImage</a></h2>
</div>

<p>BlackThresholdImage() is like ThresholdImage() but forces all pixels below the threshold into black while leaving all pixels above the threshold unchanged.</p>

<p>The format of the BlackThresholdImage method is:</p>

<pre class="code">
  MagickBooleanType BlackThresholdImage(Image *image,const char *threshold)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>threshold</h4>
<p>Define the threshold value.</p>

<div style="margin: auto;">
  <h2><a name="BlurImage">BlurImage</a></h2>
</div>

<p>BlurImage() blurs an image.  We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma).  For reasonable results, the radius should be larger than sigma.  Use a radius of 0 and BlurImage() selects a suitable radius for you.</p>

<p>BlurImage() differs from GaussianBlurImage() in that it uses a separable kernel which is faster but mathematically equivalent to the non-separable kernel.</p>

<p>The format of the BlurImage method is:</p>

<pre class="code">
  Image *BlurImage(const Image *image,const double radius,
    const double sigma,ExceptionInfo *exception)
  Image *BlurImageChannel(const Image *image,const ChannelType channel,
    const double radius,const double sigma,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>radius</h4>
<p>The radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>sigma</h4>
<p>The standard deviation of the Gaussian, in pixels.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="DespeckleImage">DespeckleImage</a></h2>
</div>

<p>DespeckleImage() reduces the speckle noise in an image while perserving the edges of the original image.</p>

<p>The format of the DespeckleImage method is:</p>

<pre class="code">
  Image *DespeckleImage(const Image *image,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="EdgeImage">EdgeImage</a></h2>
</div>

<p>EdgeImage() finds edges in an image.  Radius defines the radius of the convolution filter.  Use a radius of 0 and EdgeImage() selects a suitable radius for you.</p>

<p>The format of the EdgeImage method is:</p>

<pre class="code">
  Image *EdgeImage(const Image *image,const double radius,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>the radius of the pixel neighborhood.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="EmbossImage">EmbossImage</a></h2>
</div>

<p>EmbossImage() returns a grayscale image with a three-dimensional effect. We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma).  For reasonable results, radius should be larger than sigma.  Use a radius of 0 and Emboss() selects a suitable radius for you.</p>

<p>The format of the EmbossImage method is:</p>

<pre class="code">
  Image *EmbossImage(const Image *image,const double radius,
    const double sigma,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>the radius of the pixel neighborhood.</p>

<h4>sigma</h4>
<p>The standard deviation of the Gaussian, in pixels.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="GaussianBlurImage">GaussianBlurImage</a></h2>
</div>

<p>GaussianBlurImage() blurs an image.  We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma). For reasonable results, the radius should be larger than sigma.  Use a radius of 0 and GaussianBlurImage() selects a suitable radius for you</p>

<p>The format of the GaussianBlurImage method is:</p>

<pre class="code">
  Image *GaussianBlurImage(const Image *image,onst double radius,
    const double sigma,ExceptionInfo *exception)
  Image *GaussianBlurImageChannel(const Image *image,
    const ChannelType channel,const double radius,const double sigma,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>radius</h4>
<p>the radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>sigma</h4>
<p>the standard deviation of the Gaussian, in pixels.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="MedianFilterImage">MedianFilterImage</a></h2>
</div>

<p>MedianFilterImage() applies a digital filter that improves the quality of a noisy image.  Each pixel is replaced by the median in a set of neighboring pixels as defined by radius.</p>

<p>The algorithm was contributed by Mike Edmonds and implements an insertion sort for selecting median color-channel values.  For more on this algorithm see "Skip Lists: A probabilistic Alternative to Balanced Trees" by William Pugh in the June 1990 of Communications of the ACM.</p>

<p>The format of the MedianFilterImage method is:</p>

<pre class="code">
  Image *MedianFilterImage(const Image *image,const double radius,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>The radius of the pixel neighborhood.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="MotionBlurImage">MotionBlurImage</a></h2>
</div>

<p>MotionBlurImage() simulates motion blur.  We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma). For reasonable results, radius should be larger than sigma.  Use a radius of 0 and MotionBlurImage() selects a suitable radius for you. Angle gives the angle of the blurring motion.</p>

<p>Andrew Protano contributed this effect.</p>

<p>The format of the MotionBlurImage method is:</p>

<pre class="code">
      Image *MotionBlurImage(const Image *image,const double radius,
  const double sigma,const double angle,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>The radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>sigma</h4>
<p>The standard deviation of the Gaussian, in pixels.</p>

<h4>angle</h4>
<p>Apply the effect along this angle.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="PreviewImage">PreviewImage</a></h2>
</div>

<p>PreviewImage() tiles 9 thumbnails of the specified image with an image processing operation applied with varying parameters.  This may be helpful pin-pointing an appropriate parameter for a particular image processing operation.</p>

<p>The format of the PreviewImages method is:</p>

<pre class="code">
  Image *PreviewImages(const Image *image,const PreviewType preview,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>preview</h4>
<p>The image processing operation.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="RadialBlurImage">RadialBlurImage</a></h2>
</div>

<p>RadialBlurImage() applies a radial blur to the image.</p>

<p>Andrew Protano contributed this effect.</p>

<p>The format of the RadialBlurImage method is:</p>

<pre class="code">
      Image *RadialBlurImage(const Image *image,const double angle,
  ExceptionInfo *exception)
      Image *RadialBlurImageChannel(const Image *image,const ChannelType channel,
  const double angle,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>angle</h4>
<p>The angle of the radial blur.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="RandomThresholdImage">RandomThresholdImage</a></h2>
</div>

<p>RandomThresholdImage() changes the value of individual pixels based on the intensity of each pixel compared to a random threshold.  The result is a low-contrast, two color image.</p>

<p>The format of the RandomThresholdImage method is:</p>

<pre class="code">
  MagickBooleanType RandomThresholdImageChannel(Image *image,
    const char *thresholds,ExceptionInfo *exception)
  MagickBooleanType RandomThresholdImageChannel(Image *image,
    const ChannelType channel,const char *thresholds,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel or channels to be thresholded.</p>

<h4>thresholds</h4>
<p>a geometry string containing low,high thresholds.  If the string contains 2x2, 3x3, or 4x4, an ordered dither of order 2, 3, or 4 is performed instead.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="ReduceNoiseImage">ReduceNoiseImage</a></h2>
</div>

<p>ReduceNoiseImage() smooths the contours of an image while still preserving edge information.  The algorithm works by replacing each pixel with its neighbor closest in value.  A neighbor is defined by radius.  Use a radius of 0 and ReduceNoise() selects a suitable radius for you.</p>

<p>The format of the ReduceNoiseImage method is:</p>

<pre class="code">
  Image *ReduceNoiseImage(const Image *image,const double radius,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>The radius of the pixel neighborhood.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="ShadeImage">ShadeImage</a></h2>
</div>

<p>ShadeImage() shines a distant light on an image to create a three-dimensional effect. You control the positioning of the light with azimuth and elevation; azimuth is measured in degrees off the x axis and elevation is measured in pixels above the Z axis.</p>

<p>The format of the ShadeImage method is:</p>

<pre class="code">
  Image *ShadeImage(const Image *image,const MagickBooleanType gray,
    const double azimuth,const double elevation,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>gray</h4>
<p>A value other than zero shades the intensity of each pixel.</p>

<h4>azimuth, elevation</h4>
<p>Define the light source direction.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="SharpenImage">SharpenImage</a></h2>
</div>

<p>SharpenImage() sharpens the image.  We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma).  For reasonable results, radius should be larger than sigma.  Use a radius of 0 and SharpenImage() selects a suitable radius for you.</p>

<p>Using a separable kernel would be faster, but the negative weights cancel out on the corners of the kernel producing often undesirable ringing inthe filtered result; this can be avoided by using a 2D gaussian shaped image sharpening kernel instead.</p>

<p>The format of the SharpenImage method is:</p>

<pre class="code">
      Image *SharpenImage(const Image *image,const double radius,
  const double sigma,ExceptionInfo *exception)
      Image *SharpenImageChannel(const Image *image,const ChannelType channel,
  const double radius,const double sigma,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>radius</h4>
<p>The radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>sigma</h4>
<p>The standard deviation of the Laplacian, in pixels.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="SpreadImage">SpreadImage</a></h2>
</div>

<p>SpreadImage() is a special effects method that randomly displaces each pixel in a block defined by the radius parameter.</p>

<p>The format of the SpreadImage method is:</p>

<pre class="code">
  Image *SpreadImage(const Image *image,const double radius,
    ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>radius</h4>
<p>Choose a random pixel in a neighborhood of this extent.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="UnsharpMaskImage">UnsharpMaskImage</a></h2>
</div>

<p>UnsharpMaskImage() sharpens one or more image channels.  We convolve the image with a Gaussian operator of the given radius and standard deviation (sigma).  For reasonable results, radius should be larger than sigma.  Use a radius of 0 and UnsharpMaskImage() selects a suitable radius for you.</p>

<p>The format of the UnsharpMaskImage method is:</p>

<pre class="code">
      Image *UnsharpMaskImage(const Image *image,const double radius,
  const double sigma,const double amount,const double threshold,
  ExceptionInfo *exception)
      Image *UnsharpMaskImageChannel(const Image *image,
  const ChannelType channel,const double radius,const double sigma,
  const double amount,const double threshold,ExceptionInfo *exception)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>channel</h4>
<p>The channel type.</p>

<h4>radius</h4>
<p>The radius of the Gaussian, in pixels, not counting the center pixel.</p>

<h4>sigma</h4>
<p>The standard deviation of the Gaussian, in pixels.</p>

<h4>amount</h4>
<p>The percentage of the difference between the original and the blur image that is added back into the original.</p>

<h4>threshold</h4>
<p>The threshold in pixels needed to apply the diffence amount.</p>

<h4>exception</h4>
<p>Return any errors or warnings in this structure.</p>

<div style="margin: auto;">
  <h2><a name="WhiteThresholdImage">WhiteThresholdImage</a></h2>
</div>

<p>WhiteThresholdImage() is like ThresholdImage() but forces all pixels above the threshold into white while leaving all pixels below the threshold unchanged.</p>

<p>The format of the WhiteThresholdImage method is:</p>

<pre class="code">
  MagickBooleanType WhiteThresholdImage(Image *image,const char *threshold)
</pre>

<p>A description of each parameter follows:</p>

<h4>image</h4>
<p>The image.</p>

<h4>threshold</h4>
<p>Define the threshold value</p>

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