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147
148<p class="navigation-index">[<a href="#QuantizeImage">QuantizeImage</a> &bull; <a href="#AcquireQuantizeInfo">AcquireQuantizeInfo</a> &bull; <a href="#CloneQuantizeInfo">CloneQuantizeInfo</a> &bull; <a href="#CompressImageColormap">CompressImageColormap</a> &bull; <a href="#DestroyQuantizeInfo">DestroyQuantizeInfo</a> &bull; <a href="#GetImageQuantizeError">GetImageQuantizeError</a> &bull; <a href="#GetQuantizeInfo">GetQuantizeInfo</a> &bull; <a href="#PosterizeImage">PosterizeImage</a> &bull; <a href="#QuantizeImage">QuantizeImage</a> &bull; <a href="#QuantizeImages">QuantizeImages</a> &bull; <a href="#RemapImage">RemapImage</a> &bull; <a href="#RemapImages">RemapImages</a> &bull; <a href="#SetGrayscaleImage">SetGrayscaleImage</a>]</p>
149
150<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
151_8c.html" target="source" name="QuantizeImage">QuantizeImage</a></h2>
152<div class="doc-section">
153
154<p>QuantizeImage() takes a standard RGB or monochrome images and quantizes them down to some fixed number of colors.</p></ol>
155
156<p>For purposes of color allocation, an image is a set of n pixels, where each pixel is a point in RGB space. RGB space is a 3-dimensional vector space, and each pixel, Pi, is defined by an ordered triple of red, green, and blue coordinates, (Ri, Gi, Bi).</p></ol>
157
158<p>Each primary color component (red, green, or blue) represents an intensity which varies linearly from 0 to a maximum value, Cmax, which corresponds to full saturation of that color. Color allocation is defined over a domain consisting of the cube in RGB space with opposite vertices at (0,0,0) and (Cmax, Cmax, Cmax). QUANTIZE requires Cmax = 255.</p></ol>
159
160<p>The algorithm maps this domain onto a tree in which each node represents a cube within that domain. In the following discussion these cubes are defined by the coordinate of two opposite vertices:</p>
161
162<pre class="text">
163 the origin.
164</pre>
165
166<p>The tree's root node represents the entire domain, (0,0,0) through (Cmax,Cmax,Cmax). Each lower level in the tree is generated by subdividing one node's cube into eight smaller cubes of equal size. This corresponds to bisecting the parent cube with planes passing through the midpoints of each edge.</p></ol>
167
168<p>The basic algorithm operates in three phases: Classification, Reduction, and Assignment. Classification builds a color description tree for the image. Reduction collapses the tree until the number it represents, at most, the number of colors desired in the output image. Assignment defines the output image's color map and sets each pixel's color by restorage_class in the reduced tree. Our goal is to minimize the numerical discrepancies between the original colors and quantized colors (quantization error).</p></ol>
169
170<p>Classification begins by initializing a color description tree of sufficient depth to represent each possible input color in a leaf. However, it is impractical to generate a fully-formed color description tree in the storage_class phase for realistic values of Cmax. If colors components in the input image are quantized to k-bit precision, so that Cmax= 2k-1, the tree would need k levels below the root node to allow representing each possible input color in a leaf. This becomes prohibitive because the tree's total number of nodes is 1 + sum(i=1, k, 8k).</p></ol>
171
172<p>A complete tree would require 19,173,961 nodes for k = 8, Cmax = 255.</p>
173<h5>avoid building a fully populated tree, QUANTIZE</h5>
174<ol><p>(1) Initializes data structures for nodes only as they are needed; (2) Chooses a maximum depth for the tree as a function of the desired number of colors in the output image (currently log2(colormap size)).</p></ol>
175
176<p>For each pixel in the input image, storage_class scans downward from the root of the color description tree. At each level of the tree it identifies the single node which represents a cube in RGB space containing the pixel's color. It updates the following data for each such node:</p>
177
178<pre class="text">
179 n1: Number of pixels whose color is contained in the RGB cube which
180 this node represents;
181</pre>
182
183<p>n2: Number of pixels whose color is not represented in a node at lower depth in the tree; initially, n2 = 0 for all nodes except leaves of the tree.</p></ol>
184
185<p>Sr, Sg, Sb: Sums of the red, green, and blue component values for all pixels not classified at a lower depth. The combination of these sums and n2 will ultimately characterize the mean color of a set of pixels represented by this node.</p></ol>
186
187<p>E: the distance squared in RGB space between each pixel contained within a node and the nodes' center. This represents the quantization error for a node.</p></ol>
188
189<p>Reduction repeatedly prunes the tree until the number of nodes with n2 > 0 is less than or equal to the maximum number of colors allowed in the output image. On any given iteration over the tree, it selects those nodes whose E count is minimal for pruning and merges their color statistics upward. It uses a pruning threshold, Ep, to govern node selection as follows:</p></ol>
190
191<p>Ep = 0 while number of nodes with (n2 > 0) > required maximum number of colors prune all nodes such that E <= Ep Set Ep to minimum E in remaining nodes</p></ol>
192
193<p>This has the effect of minimizing any quantization error when merging two nodes together.</p></ol>
194
195<p>When a node to be pruned has offspring, the pruning procedure invokes itself recursively in order to prune the tree from the leaves upward. n2, Sr, Sg, and Sb in a node being pruned are always added to the corresponding data in that node's parent. This retains the pruned node's color characteristics for later averaging.</p></ol>
196
197<p>For each node, n2 pixels exist for which that node represents the smallest volume in RGB space containing those pixel's colors. When n2 > 0 the node will uniquely define a color in the output image. At the beginning of reduction, n2 = 0 for all nodes except a the leaves of the tree which represent colors present in the input image.</p></ol>
198
199<p>The other pixel count, n1, indicates the total number of colors within the cubic volume which the node represents. This includes n1 - n2 pixels whose colors should be defined by nodes at a lower level in the tree.</p></ol>
200
201<p>Assignment generates the output image from the pruned tree. The output</p>
202<h5>parts</h5>
203<ol><p>(1) A color map, which is an array of color descriptions (RGB triples) for each color present in the output image; (2) A pixel array, which represents each pixel as an index into the color map array.</p></ol>
204
205<p>First, the assignment phase makes one pass over the pruned color description tree to establish the image's color map. For each node with n2 > 0, it divides Sr, Sg, and Sb by n2 . This produces the mean color of all pixels that classify no lower than this node. Each of these colors becomes an entry in the color map.</p></ol>
206
207<p>Finally, the assignment phase reclassifies each pixel in the pruned tree to identify the deepest node containing the pixel's color. The pixel's value in the pixel array becomes the index of this node's mean color in the color map.</p></ol>
208
209<p>This method is based on a similar algorithm written by Paul Raveling.</p></ol>
210
211 </div>
212<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
213_8c.html" target="source" name="AcquireQuantizeInfo">AcquireQuantizeInfo</a></h2>
214<div class="doc-section">
215
216<p>AcquireQuantizeInfo() allocates the QuantizeInfo structure.</p></ol>
217
218<p>The format of the AcquireQuantizeInfo method is:</p>
219
220<pre class="code">
221 QuantizeInfo *AcquireQuantizeInfo(const ImageInfo *image_info)
222</pre>
223
224<p>A description of each parameter follows:</p></ol>
225
226<h5>image_info</h5>
227<ol><p>the image info.</p></ol>
228
229 </div>
230<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
231_8c.html" target="source" name="CloneQuantizeInfo">CloneQuantizeInfo</a></h2>
232<div class="doc-section">
233
234<p>CloneQuantizeInfo() makes a duplicate of the given quantize info structure, or if quantize info is NULL, a new one.</p></ol>
235
236<p>The format of the CloneQuantizeInfo method is:</p>
237
238<pre class="code">
239 QuantizeInfo *CloneQuantizeInfo(const QuantizeInfo *quantize_info)
240</pre>
241
242<p>A description of each parameter follows:</p></ol>
243
244<h5>clone_info</h5>
245<ol><p>Method CloneQuantizeInfo returns a duplicate of the given quantize info, or if image info is NULL a new one.</p></ol>
246
247<h5>quantize_info</h5>
248<ol><p>a structure of type info.</p></ol>
249
250 </div>
251<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
252_8c.html" target="source" name="CompressImageColormap">CompressImageColormap</a></h2>
253<div class="doc-section">
254
255<p>CompressImageColormap() compresses an image colormap by removing any duplicate or unused color entries.</p></ol>
256
257<p>The format of the CompressImageColormap method is:</p>
258
259<pre class="code">
260 MagickBooleanType CompressImageColormap(Image *image)
261</pre>
262
263<p>A description of each parameter follows:</p></ol>
264
265<h5>image</h5>
266<ol><p>the image.</p></ol>
267
268 </div>
269<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
270_8c.html" target="source" name="DestroyQuantizeInfo">DestroyQuantizeInfo</a></h2>
271<div class="doc-section">
272
273<p>DestroyQuantizeInfo() deallocates memory associated with an QuantizeInfo structure.</p></ol>
274
275<p>The format of the DestroyQuantizeInfo method is:</p>
276
277<pre class="code">
278 QuantizeInfo *DestroyQuantizeInfo(QuantizeInfo *quantize_info)
279</pre>
280
281<p>A description of each parameter follows:</p></ol>
282
283<h5>quantize_info</h5>
284<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
285
286 </div>
287<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
288_8c.html" target="source" name="GetImageQuantizeError">GetImageQuantizeError</a></h2>
289<div class="doc-section">
290
291<p>GetImageQuantizeError() measures the difference between the original and quantized images. This difference is the total quantization error. The error is computed by summing over all pixels in an image the distance squared in RGB space between each reference pixel value and its quantized value. These values are computed:</p>
292
293<pre class="text">
294 o mean_error_per_pixel: This value is the mean error for any single
295 pixel in the image.
296</pre>
297
298<h5>normalized_mean_square_error</h5>
299<ol><p>This value is the normalized mean quantization error for any single pixel in the image. This distance measure is normalized to a range between 0 and 1. It is independent of the range of red, green, and blue values in the image.</p></ol>
300
301<h5>normalized_maximum_square_error</h5>
302<ol><p>Thsi value is the normalized maximum quantization error for any single pixel in the image. This distance measure is normalized to a range between 0 and 1. It is independent of the range of red, green, and blue values in your image.</p></ol>
303
304<p>The format of the GetImageQuantizeError method is:</p>
305
306<pre class="code">
307 MagickBooleanType GetImageQuantizeError(Image *image)
308</pre>
309
310<p>A description of each parameter follows.</p></ol>
311
312<h5>image</h5>
313<ol><p>the image.</p></ol>
314
315 </div>
316<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
317_8c.html" target="source" name="GetQuantizeInfo">GetQuantizeInfo</a></h2>
318<div class="doc-section">
319
320<p>GetQuantizeInfo() initializes the QuantizeInfo structure.</p></ol>
321
322<p>The format of the GetQuantizeInfo method is:</p>
323
324<pre class="code">
325 GetQuantizeInfo(QuantizeInfo *quantize_info)
326</pre>
327
328<p>A description of each parameter follows:</p></ol>
329
330<h5>quantize_info</h5>
331<ol><p>Specifies a pointer to a QuantizeInfo structure.</p></ol>
332
333 </div>
334<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
335_8c.html" target="source" name="PosterizeImage">PosterizeImage</a></h2>
336<div class="doc-section">
337
338<p>PosterizeImage() reduces the image to a limited number of colors for a "poster" effect.</p></ol>
339
340<p>The format of the PosterizeImage method is:</p>
341
342<pre class="code">
343 MagickBooleanType PosterizeImage(Image *image,const unsigned long levels,
344 const MagickBooleanType dither)
345</pre>
346
347<p>A description of each parameter follows:</p></ol>
348
349<h5>image</h5>
350<ol><p>Specifies a pointer to an Image structure.</p></ol>
351
352<h5>levels</h5>
353<ol><p>Number of color levels allowed in each channel. Very low values (2, 3, or 4) have the most visible effect.</p></ol>
354
355<h5>dither</h5>
356<ol><p>Set this integer value to something other than zero to dither the mapped image.</p></ol>
357
358 </div>
359<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
360_8c.html" target="source" name="QuantizeImage">QuantizeImage</a></h2>
361<div class="doc-section">
362
363<p>QuantizeImage() analyzes the colors within a reference image and chooses a fixed number of colors to represent the image. The goal of the algorithm is to minimize the color difference between the input and output image while minimizing the processing time.</p></ol>
364
365<p>The format of the QuantizeImage method is:</p>
366
367<pre class="code">
368 MagickBooleanType QuantizeImage(const QuantizeInfo *quantize_info,
369 Image *image)
370</pre>
371
372<p>A description of each parameter follows:</p></ol>
373
374<h5>quantize_info</h5>
375<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
376
377<h5>image</h5>
378<ol><p>the image.</p></ol>
379
380 </div>
381<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
382_8c.html" target="source" name="QuantizeImages">QuantizeImages</a></h2>
383<div class="doc-section">
384
385<p>QuantizeImages() analyzes the colors within a set of reference images and chooses a fixed number of colors to represent the set. The goal of the algorithm is to minimize the color difference between the input and output images while minimizing the processing time.</p></ol>
386
387<p>The format of the QuantizeImages method is:</p>
388
389<pre class="code">
390 MagickBooleanType QuantizeImages(const QuantizeInfo *quantize_info,
391 Image *images)
392</pre>
393
394<p>A description of each parameter follows:</p></ol>
395
396<h5>quantize_info</h5>
397<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
398
399<h5>images</h5>
400<ol><p>Specifies a pointer to a list of Image structures.</p></ol>
401
402 </div>
403<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
404_8c.html" target="source" name="RemapImage">RemapImage</a></h2>
405<div class="doc-section">
406
407<p>RemapImage() replaces the colors of an image with the closest color from a reference image.</p></ol>
408
409<p>The format of the RemapImage method is:</p>
410
411<pre class="code">
412 MagickBooleanType RemapImage(const QuantizeInfo *quantize_info,
413 Image *image,const Image *remap_image)
414</pre>
415
416<p>A description of each parameter follows:</p></ol>
417
418<h5>quantize_info</h5>
419<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
420
421<h5>image</h5>
422<ol><p>the image.</p></ol>
423
424<h5>remap_image</h5>
425<ol><p>the reference image.</p></ol>
426
427 </div>
428<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
429_8c.html" target="source" name="RemapImages">RemapImages</a></h2>
430<div class="doc-section">
431
432<p>RemapImages() replaces the colors of a sequence of images with the closest color from a reference image.</p></ol>
433
434<p>The format of the RemapImage method is:</p>
435
436<pre class="code">
437 MagickBooleanType RemapImages(const QuantizeInfo *quantize_info,
438 Image *images,Image *remap_image)
439</pre>
440
441<p>A description of each parameter follows:</p></ol>
442
443<h5>quantize_info</h5>
444<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
445
446<h5>images</h5>
447<ol><p>the image sequence.</p></ol>
448
449<h5>remap_image</h5>
450<ol><p>the reference image.</p></ol>
451
452 </div>
453<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
454_8c.html" target="source" name="SetGrayscaleImage">SetGrayscaleImage</a></h2>
455<div class="doc-section">
456
457<p>SetGrayscaleImage() converts an image to a PseudoClass grayscale image.</p></ol>
458
459<p>The format of the SetGrayscaleImage method is:</p>
460
461<pre class="code">
462 MagickBooleanType SetGrayscaleImage(Image *image)
463</pre>
464
465<p>A description of each parameter follows:</p></ol>
466
467<h5>image</h5>
468<ol><p>The image.</p></ol>
469
470 </div>
471
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