/*
* $RCSfile: ColorQuantizerDescriptor.java,v $
*
* Copyright (c) 2005 Sun Microsystems, Inc. All rights reserved.
*
* Use is subject to license terms.
*
* $Revision: 1.1 $
* $Date: 2005/02/11 04:57:31 $
* $State: Exp $
*/
package com.lightcrafts.mediax.jai.operator;
import java.awt.RenderingHints;
import java.awt.image.RenderedImage;
import java.awt.image.renderable.ParameterBlock;
import com.lightcrafts.mediax.jai.JAI;
import com.lightcrafts.mediax.jai.OperationDescriptorImpl;
import com.lightcrafts.mediax.jai.ParameterBlockJAI;
import com.lightcrafts.mediax.jai.RenderedOp;
import com.lightcrafts.mediax.jai.ROI;
import com.lightcrafts.mediax.jai.util.Range;
import com.lightcrafts.mediax.jai.registry.RenderedRegistryMode;
/**
* This <code>OperationDescriptor</code> defines the "ColorQuantizer"
* operation.
*
* <p> This operation generates an optimal lookup table (LUT) based on
* the provided 3-band RGB source image by executing a color
* quantization algorithm. This LUT is stored in the property
* "JAI.LookupTable" that has a type of <code>LookupTableJAI</code>.
* Thus, it can be retrieved by means of <code>getProperty</code>.
* This LUT can be further utilized in other operations such as
* "errordiffusion" to convert the 3-band RGB image into a high-quality
* color-indexed image. The computation of the LUT can be deferred by
* defining a <code>DeferredProperty</code> from the property
* "JAI.LookupTable" and providing that as the parameter value for
* "errordiffusion". This operation also creates a color-indexed
* destination image based on the nearest distance classification (without
* dithering). However, the quality of this classification result may
* not be as good as the result of "errordiffusion".
*
* <p> The supported source image data type is implementation-dependent.
* For example, the Sun implementation will support only the byte type.
*
* <p> The data set used in the color quantization can be defined by
* the optional parameters <code>xPeriod</code>, <code>yPeriod</code>
* and <code>ROI</code>. If these parameters are provided, the pixels in
* the subsampled image (and in the ROI) will be used to compute the
* LUT.
*
* <p> Three built-in color quantization algorithms are supported by
* this operation: Paul Heckbert's median-cut algorithm, Anthony Dekker's
* NeuQuant algorithm, and the Oct-Tree color quantization algorithm of
* Gervautz and Purgathofer.
*
* <p> The median-cut color quantization computes the 3D color histogram
* first, then chooses and divides the largest color cube (in number of pixels)
* along the median, until the required number of clusters is obtained
* or all the cubes are not separable. The NeuQuant algorithm creates
* the cluster centers using Kohonen's self-organizing neural network.
* The Oct-Tree color quantization constructs an oct-tree of the
* color histogram, then repeatedly merges the offspring into the parent
* if they contain a number of pixels smaller than a threshold. With the
* equivalent parameters, the median-cut algorithm is the fastest, and the
* NeuQuant algorithm is the slowest. However, NeuQuant algorithm can
* still generate a good result with a relatively high subsample rate, which
* is useful for large images.
* In these three algorithms, the Oct-Tree algorithm is the most space
* consuming one. For further details of these algorithms,
* please refer to the following references:
* <table border=1>
* <tr>
* <th>Algorithm</th>
* <th>References</th>
* </tr>
* <tr>
* <td>Median-Cut</td>
* <td>Color Image Quantization for Frame Buffer
* Display, Paul Heckbert, SIGGRAPH proceedings, 1982, pp. 297-307
* </td></tr>
* <tr>
* <td>NeuQuant</td>
* <td>Kohonen Neural Networks for Optimal Colour Quantization,
* Anthony Dekker, In <i>Network: Computation in Neural Systems</i>,
* Volume 5, Institute of Physics Publishing, 1994, pp 351-367.
* </td>
* </tr>
* <tr>
* <td>Oct-Tree</td>
* <td><i>Interactive Computer Graphics: Functional, Procedural, and
* Device-Level Methods</i> by Peter Burger and Duncan Gillis,
* Addison-Wesley, 1989, pp 345.
* </td>
* </tr>
*</table>
*
* <p> The generated LUT may have fewer entries than expected. For
* example, the source image might not have as many colors as expected.
* In the oct-tree algorithm, all the offspring of a node are merged
* if they contain a number of pixels smaller than a threshold. This
* may result in slightly fewer colors than expected.
*
* <p> The learning procedure of the NeuQuant algorithm randomly goes
* through all the pixels in the training data set. To simplify and
* speed up the implementation, the bounding rectangle of the
* provided ROI may be used (by the implementation) to define the
* training data set instead of the ROI itself.
*
* <p><table border=1>
* <caption>Resource List</caption>
* <tr><th>Name</th> <th>Value</th></tr>
* <tr><td>GlobalName</td> <td>ColorQuantizer</td></tr>
* <tr><td>LocalName</td> <td>ColorQuantizer</td></tr>
* <tr><td>Vendor</td> <td>com.lightcrafts.media.jai</td></tr>
* <tr><td>Description</td> <td>Generates an optimal LUT by executing a
* color quantization algorithm, and a
* color-indexed image by the nearest distance
* classification.</td></tr>
* <tr><td>DocURL</td> <td>http://java.sun.com/products/java-media/jai/forDevelopers/jai-apidocs/javax/media/jai/operator/ColorQuantizerDescriptor.html</td></tr>
* <tr><td>Version</td> <td>1.1</td></tr>
* <tr><td>arg0Desc</td> <td>The color quantization algorithm name. One of
* ColorQuantizerDescriptor.MEDIANCUT,
* ColorQuantizerDescriptor.NEUQUANT, or
* ColorQuantizerDescriptor.OCTTREE</td></tr>
* <tr><td>arg1Desc</td> <td>The maximum color number, that is, the expected
* number of colors in the result image.</td></tr>
* <tr><td>arg2Desc</td> <td>This is an algorithm-dependent parameter. For
* the median-cut color quantization, it is the
* maximum size of the three-dimensional
* histogram.
* For the neuquant color quantization, it is the
* number of cycles. For the oct-tree color
* quantization, it is the maximum size of the
* oct-tree.</td></tr>
* <tr><td>arg3Desc</td> <td>The ROI in which the pixels are involved into
* the color quantization.</td></tr>
* <tr><td>arg4Desc</td> <td>The subsample rate in x direction.</td></tr>
* <tr><td>arg4Desc</td> <td>The subsample rate in y direction.</td></tr>
* </table></p>
*
* <p><table border=1>
* <caption>Parameter List</caption>
* <tr><th>Name</th> <th>Class Type</th>
* <th>Default Value</th></tr>
* <tr><td>quantizationAlgorithm</td>
* <td>com.lightcrafts.mediax.jai.operator.ColorQuantizerType</td>
* <td>ColorQuantizerDescriptor.MEDIANCUT</td>
* <tr><td>maxColorNum</td> <td>java.lang.Integer</td>
* <td>256</td>
* <tr><td>upperBound</td> <td>java.lang.Integer</td>
* <td>32768 for median-cut, 100 for neuquant,
* 65536 for oct-tree</td>
* <tr><td>roi</td> <td>com.lightcrafts.mediax.jai.ROI</td>
* <td>null</td>
* <tr><td>xPeriod</td> <td>java.lang.Integer</td>
* <td>1</td>
* <tr><td>yPeriod</td> <td>java.lang.Integer</td>
* <td>1</td>
* </table></p>
*
* @see com.lightcrafts.mediax.jai.ROI
* @see com.lightcrafts.mediax.jai.OperationDescriptor
*
* @since JAI 1.1.2
*/
public class ColorQuantizerDescriptor extends OperationDescriptorImpl {
/** The predefined color quantization algorithms. */
/** The pre-defined median-cut color quantization algorithm. */
public static final ColorQuantizerType MEDIANCUT =
new ColorQuantizerType("MEDIANCUT", 1);
/** The pre-defined NeuQuant color quantization algorithm. */
public static final ColorQuantizerType NEUQUANT =
new ColorQuantizerType("NEUQUANT", 2);
/** The pre-defined Oct-Tree color quantization algorithm. */
public static final ColorQuantizerType OCTTREE =
new ColorQuantizerType("OCTTREE", 3);
/**
* The resource strings that provide the general documentation
* and specify the parameter list for this operation.
*/
private static final String[][] resources = {
{"GlobalName", "ColorQuantizer"},
{"LocalName", "ColorQuantizer"},
{"Vendor", "com.lightcrafts.media.jai"},
{"Description", JaiI18N.getString("ColorQuantizerDescriptor0")},
{"DocURL", "http://java.sun.com/products/java-media/jai/forDevelopers/jai-apidocs/javax/media/jai/operator/ColorQuantizerDescriptor.html"},
{"Version", JaiI18N.getString("DescriptorVersion2")},
{"arg0Desc", JaiI18N.getString("ColorQuantizerDescriptor1")},
{"arg1Desc", JaiI18N.getString("ColorQuantizerDescriptor2")},
{"arg2Desc", JaiI18N.getString("ColorQuantizerDescriptor3")},
{"arg3Desc", JaiI18N.getString("ColorQuantizerDescriptor4")},
{"arg4Desc", JaiI18N.getString("ColorQuantizerDescriptor5")},
{"arg5Desc", JaiI18N.getString("ColorQuantizerDescriptor6")},
};
/** The parameter name list for this operation. */
private static final String[] paramNames = {
"quantizationAlgorithm",
"maxColorNum",
"upperBound",
"roi",
"xPeriod",
"yPeriod"
};
/** The parameter class list for this operation. */
private static final Class[] paramClasses = {
com.lightcrafts.mediax.jai.operator.ColorQuantizerType.class,
java.lang.Integer.class,
java.lang.Integer.class,
com.lightcrafts.mediax.jai.ROI.class,
java.lang.Integer.class,
java.lang.Integer.class
};
/** The parameter default value list for this operation. */
private static final Object[] paramDefaults = {
MEDIANCUT,
new Integer(256),
null,
null,
new Integer(1),
new Integer(1)
};
private static final String[] supportedModes = {
"rendered"
};
/** Constructor. */
public ColorQuantizerDescriptor() {
super(resources, supportedModes, 1,
paramNames, paramClasses, paramDefaults, null);
}
/**
* Returns the minimum legal value of a specified numeric parameter
* for this operation.
*/
public Range getParamValueRange(int index) {
switch (index) {
case 1:
case 2:
case 4:
case 5:
return new Range(Integer.class, new Integer(1), null);
}
return null;
}
/**
* Returns <code>true</code> if this operation is capable of handling
* the input parameters.
*
* <p> In addition to the default validations done in the super class,
* this method verifies that the provided quantization algorithm is one of
* the three predefined algorithms in this class.
*
* @throws IllegalArgumentException If <code>args</code> is <code>null</code>.
* @throws IllegalArgumentException If <code>msg</code> is <code>null</code>
* and the validation fails.
*/
protected boolean validateParameters(String modeName,
ParameterBlock args,
StringBuffer msg) {
if ( args == null || msg == null ) {
throw new IllegalArgumentException(JaiI18N.getString("Generic0"));
}
if (!super.validateParameters(modeName, args, msg))
return false;
ColorQuantizerType algorithm =
(ColorQuantizerType)args.getObjectParameter(0);
if (algorithm != MEDIANCUT && algorithm != NEUQUANT &&
algorithm != OCTTREE) {
msg.append(getName() + " " +
JaiI18N.getString("ColorQuantizerDescriptor7"));
return false;
}
Integer secondOne = (Integer)args.getObjectParameter(2);
if (secondOne == null) {
int upperBound = 0;
if (algorithm.equals(MEDIANCUT))
upperBound = 32768;
else if (algorithm.equals(NEUQUANT)) // set the cycle for train to 100
upperBound = 100;
else if (algorithm.equals(OCTTREE)) // set the maximum tree size to 65536
upperBound = 65536;
args.set(upperBound, 2);
}
return true;
}
/**
* Color quantization on the provided image.
*
* <p>Creates a <code>ParameterBlockJAI</code> from all
* supplied arguments except <code>hints</code> and invokes
* {@link JAI#create(String,ParameterBlock,RenderingHints)}.
*
* @see JAI
* @see ParameterBlockJAI
* @see RenderedOp
*
* @param source0 <code>RenderedImage</code> source 0.
* @param algorithm The algorithm to be chosen. May be <code>null</code>.
* @param maxColorNum The maximum color number. May be <code>null</code>.
* @param upperBound An algorithm-dependent parameter. See the parameter
* table above. May be <code>null</code>.
* @param roi The region of interest. May be <code>null</code>.
* @param xPeriod The X subsample rate. May be <code>null</code>.
* @param yPeriod The Y subsample rate. May be <code>null</code>.
* @param hints The <code>RenderingHints</code> to use.
* May be <code>null</code>.
* @return The <code>RenderedOp</code> destination.
* @throws IllegalArgumentException if <code>source0</code> is <code>null</code>.
*/
public static RenderedOp create(RenderedImage source0,
ColorQuantizerType algorithm,
Integer maxColorNum,
Integer upperBound,
ROI roi,
Integer xPeriod,
Integer yPeriod,
RenderingHints hints) {
ParameterBlockJAI pb =
new ParameterBlockJAI("ColorQuantizer",
RenderedRegistryMode.MODE_NAME);
pb.setSource("source0", source0);
pb.setParameter("quantizationAlgorithm", algorithm);
pb.setParameter("maxColorNum", maxColorNum);
pb.setParameter("upperBound", upperBound);
pb.setParameter("roi", roi);
pb.setParameter("xPeriod", xPeriod);
pb.setParameter("yPeriod", yPeriod);
return JAI.create("ColorQuantizer", pb, hints);
}
}