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java.lang.Object | +--javax.media.jai.OperationDescriptorImpl | +--javax.media.jai.operator.ColorQuantizerDescriptor
This OperationDescriptor
defines the "ColorQuantizer"
operation.
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 LookupTableJAI
.
Thus, it can be retrieved by means of getProperty
.
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 DeferredProperty
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".
The supported source image data type is implementation-dependent. For example, the Sun implementation will support only the byte type.
The data set used in the color quantization can be defined by
the optional parameters xPeriod
, yPeriod
and ROI
. If these parameters are provided, the pixels in
the subsampled image (and in the ROI) will be used to compute the
LUT.
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.
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:
Algorithm | References |
---|---|
Median-Cut | Color Image Quantization for Frame Buffer Display, Paul Heckbert, SIGGRAPH proceedings, 1982, pp. 297-307 |
NeuQuant | Kohonen Neural Networks for Optimal Colour Quantization, Anthony Dekker, In Network: Computation in Neural Systems, Volume 5, Institute of Physics Publishing, 1994, pp 351-367. |
Oct-Tree | Interactive Computer Graphics: Functional, Procedural, and Device-Level Methods by Peter Burger and Duncan Gillis, Addison-Wesley, 1989, pp 345. |
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.
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.
Name | Value |
---|---|
GlobalName | ColorQuantizer |
LocalName | ColorQuantizer |
Vendor | com.sun.media.jai |
Description | Generates an optimal LUT by executing a color quantization algorithm, and a color-indexed image by the nearest distance classification. |
DocURL | http://java.sun.com/products/java-media/jai/forDevelopers/jai-apidocs/javax/media/jai/operator/ColorQuantizerDescriptor.html |
Version | 1.1 |
arg0Desc | The color quantization algorithm name. One of ColorQuantizerDescriptor.MEDIANCUT, ColorQuantizerDescriptor.NEUQUANT, or ColorQuantizerDescriptor.OCTTREE |
arg1Desc | The maximum color number, that is, the expected number of colors in the result image. |
arg2Desc | 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. |
arg3Desc | The ROI in which the pixels are involved into the color quantization. |
arg4Desc | The subsample rate in x direction. |
arg4Desc | The subsample rate in y direction. |
Name | Class Type | Default Value |
---|---|---|
quantizationAlgorithm | javax.media.jai.operator.ColorQuantizerType | ColorQuantizerDescriptor.MEDIANCUT |
maxColorNum | java.lang.Integer | 256 |
upperBound | java.lang.Integer | 32768 for median-cut, 100 for neuquant, 65536 for oct-tree |
roi | javax.media.jai.ROI | null |
xPeriod | java.lang.Integer | 1 |
yPeriod | java.lang.Integer | 1 |
ROI
,
OperationDescriptor
, Serialized FormField Summary | |
static ColorQuantizerType |
MEDIANCUT
The pre-defined median-cut color quantization algorithm. |
static ColorQuantizerType |
NEUQUANT
The pre-defined NeuQuant color quantization algorithm. |
static ColorQuantizerType |
OCTTREE
The pre-defined Oct-Tree color quantization algorithm. |
Fields inherited from class javax.media.jai.OperationDescriptorImpl |
resources, sourceNames, supportedModes |
Fields inherited from interface javax.media.jai.OperationDescriptor |
NO_PARAMETER_DEFAULT |
Constructor Summary | |
ColorQuantizerDescriptor()
Constructor. |
Method Summary | |
static RenderedOp |
create(RenderedImage source0,
ColorQuantizerType algorithm,
Integer maxColorNum,
Integer upperBound,
ROI roi,
Integer xPeriod,
Integer yPeriod,
RenderingHints hints)
Color quantization on the provided image. |
Range |
getParamValueRange(int index)
Returns the minimum legal value of a specified numeric parameter for this operation. |
protected boolean |
validateParameters(String modeName,
ParameterBlock args,
StringBuffer msg)
Returns true if this operation is capable of handling
the input parameters. |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Field Detail |
public static final ColorQuantizerType MEDIANCUT
public static final ColorQuantizerType NEUQUANT
public static final ColorQuantizerType OCTTREE
Constructor Detail |
public ColorQuantizerDescriptor()
Method Detail |
public Range getParamValueRange(int index)
protected boolean validateParameters(String modeName, ParameterBlock args, StringBuffer msg)
true
if this operation is capable of handling
the input parameters.
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.
validateParameters
in class OperationDescriptorImpl
IllegalArgumentException
- If args
is null
.IllegalArgumentException
- If msg
is null
and the validation fails.public static RenderedOp create(RenderedImage source0, ColorQuantizerType algorithm, Integer maxColorNum, Integer upperBound, ROI roi, Integer xPeriod, Integer yPeriod, RenderingHints hints)
Creates a ParameterBlockJAI
from all
supplied arguments except hints
and invokes
JAI.create(String,ParameterBlock,RenderingHints)
.
source0
- RenderedImage
source 0.algorithm
- The algorithm to be chosen. May be null
.maxColorNum
- The maximum color number. May be null
.upperBound
- An algorithm-dependent parameter. See the parameter
table above. May be null
.roi
- The region of interest. May be null
.xPeriod
- The X subsample rate. May be null
.yPeriod
- The Y subsample rate. May be null
.hints
- The RenderingHints
to use.
May be null
.RenderedOp
destination.IllegalArgumentException
- if source0
is null
.JAI
,
ParameterBlockJAI
,
RenderedOp
|
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