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176
cristy307ba182010-12-25 01:00:34 +0000[diff] [blame]177<h1>Module quantize
178 Methods</h1>
cristy3ed852e2009-09-05 21:47:34 +0000[diff] [blame]179<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>
180
181<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
182_8c.html" target="source" name="QuantizeImage">QuantizeImage</a></h2>
183<div class="doc-section">
184
185<p>QuantizeImage() takes a standard RGB or monochrome images and quantizes them down to some fixed number of colors.</p></ol>
186
187<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>
188
189<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>
190
191<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>
192
193<pre class="text">
194 the origin.
195</pre>
196
197<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>
198
199<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>
200
201<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>
202
203<p>A complete tree would require 19,173,961 nodes for k = 8, Cmax = 255.</p>
204<h5>avoid building a fully populated tree, QUANTIZE</h5>
205<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>
206
207<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>
208
209<pre class="text">
210 n1: Number of pixels whose color is contained in the RGB cube which
211 this node represents;
212</pre>
213
214<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>
215
216<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>
217
218<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>
219
220<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>
221
222<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>
223
224<p>This has the effect of minimizing any quantization error when merging two nodes together.</p></ol>
225
226<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>
227
228<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>
229
230<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>
231
232<p>Assignment generates the output image from the pruned tree. The output</p>
233<h5>parts</h5>
234<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>
235
236<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>
237
238<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>
239
240<p>This method is based on a similar algorithm written by Paul Raveling.</p></ol>
241
242 </div>
243<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
244_8c.html" target="source" name="AcquireQuantizeInfo">AcquireQuantizeInfo</a></h2>
245<div class="doc-section">
246
247<p>AcquireQuantizeInfo() allocates the QuantizeInfo structure.</p></ol>
248
249<p>The format of the AcquireQuantizeInfo method is:</p>
250
251<pre class="code">
252 QuantizeInfo *AcquireQuantizeInfo(const ImageInfo *image_info)
253</pre>
254
255<p>A description of each parameter follows:</p></ol>
256
257<h5>image_info</h5>
258<ol><p>the image info.</p></ol>
259
260 </div>
261<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
262_8c.html" target="source" name="CloneQuantizeInfo">CloneQuantizeInfo</a></h2>
263<div class="doc-section">
264
265<p>CloneQuantizeInfo() makes a duplicate of the given quantize info structure, or if quantize info is NULL, a new one.</p></ol>
266
267<p>The format of the CloneQuantizeInfo method is:</p>
268
269<pre class="code">
270 QuantizeInfo *CloneQuantizeInfo(const QuantizeInfo *quantize_info)
271</pre>
272
273<p>A description of each parameter follows:</p></ol>
274
275<h5>clone_info</h5>
276<ol><p>Method CloneQuantizeInfo returns a duplicate of the given quantize info, or if image info is NULL a new one.</p></ol>
277
278<h5>quantize_info</h5>
279<ol><p>a structure of type info.</p></ol>
280
281 </div>
282<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
283_8c.html" target="source" name="CompressImageColormap">CompressImageColormap</a></h2>
284<div class="doc-section">
285
286<p>CompressImageColormap() compresses an image colormap by removing any duplicate or unused color entries.</p></ol>
287
288<p>The format of the CompressImageColormap method is:</p>
289
290<pre class="code">
291 MagickBooleanType CompressImageColormap(Image *image)
292</pre>
293
294<p>A description of each parameter follows:</p></ol>
295
296<h5>image</h5>
297<ol><p>the image.</p></ol>
298
299 </div>
300<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
301_8c.html" target="source" name="DestroyQuantizeInfo">DestroyQuantizeInfo</a></h2>
302<div class="doc-section">
303
304<p>DestroyQuantizeInfo() deallocates memory associated with an QuantizeInfo structure.</p></ol>
305
306<p>The format of the DestroyQuantizeInfo method is:</p>
307
308<pre class="code">
309 QuantizeInfo *DestroyQuantizeInfo(QuantizeInfo *quantize_info)
310</pre>
311
312<p>A description of each parameter follows:</p></ol>
313
314<h5>quantize_info</h5>
315<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
316
317 </div>
318<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
319_8c.html" target="source" name="GetImageQuantizeError">GetImageQuantizeError</a></h2>
320<div class="doc-section">
321
322<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>
323
324<pre class="text">
325 o mean_error_per_pixel: This value is the mean error for any single
326 pixel in the image.
327</pre>
328
329<h5>normalized_mean_square_error</h5>
330<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>
331
332<h5>normalized_maximum_square_error</h5>
333<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>
334
335<p>The format of the GetImageQuantizeError method is:</p>
336
337<pre class="code">
338 MagickBooleanType GetImageQuantizeError(Image *image)
339</pre>
340
341<p>A description of each parameter follows.</p></ol>
342
343<h5>image</h5>
344<ol><p>the image.</p></ol>
345
346 </div>
347<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
348_8c.html" target="source" name="GetQuantizeInfo">GetQuantizeInfo</a></h2>
349<div class="doc-section">
350
351<p>GetQuantizeInfo() initializes the QuantizeInfo structure.</p></ol>
352
353<p>The format of the GetQuantizeInfo method is:</p>
354
355<pre class="code">
356 GetQuantizeInfo(QuantizeInfo *quantize_info)
357</pre>
358
359<p>A description of each parameter follows:</p></ol>
360
361<h5>quantize_info</h5>
362<ol><p>Specifies a pointer to a QuantizeInfo structure.</p></ol>
363
364 </div>
365<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
366_8c.html" target="source" name="PosterizeImage">PosterizeImage</a></h2>
367<div class="doc-section">
368
369<p>PosterizeImage() reduces the image to a limited number of colors for a "poster" effect.</p></ol>
370
371<p>The format of the PosterizeImage method is:</p>
372
373<pre class="code">
cristybb503372010-05-27 20:51:26 +0000[diff] [blame]374 MagickBooleanType PosterizeImage(Image *image,const size_t levels,
cristy3ed852e2009-09-05 21:47:34 +0000[diff] [blame]375 const MagickBooleanType dither)
376</pre>
377
378<p>A description of each parameter follows:</p></ol>
379
380<h5>image</h5>
381<ol><p>Specifies a pointer to an Image structure.</p></ol>
382
383<h5>levels</h5>
384<ol><p>Number of color levels allowed in each channel. Very low values (2, 3, or 4) have the most visible effect.</p></ol>
385
386<h5>dither</h5>
387<ol><p>Set this integer value to something other than zero to dither the mapped image.</p></ol>
388
389 </div>
390<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
391_8c.html" target="source" name="QuantizeImage">QuantizeImage</a></h2>
392<div class="doc-section">
393
394<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>
395
396<p>The format of the QuantizeImage method is:</p>
397
398<pre class="code">
399 MagickBooleanType QuantizeImage(const QuantizeInfo *quantize_info,
400 Image *image)
401</pre>
402
403<p>A description of each parameter follows:</p></ol>
404
405<h5>quantize_info</h5>
406<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
407
408<h5>image</h5>
409<ol><p>the image.</p></ol>
410
411 </div>
412<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
413_8c.html" target="source" name="QuantizeImages">QuantizeImages</a></h2>
414<div class="doc-section">
415
416<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>
417
418<p>The format of the QuantizeImages method is:</p>
419
420<pre class="code">
421 MagickBooleanType QuantizeImages(const QuantizeInfo *quantize_info,
422 Image *images)
423</pre>
424
425<p>A description of each parameter follows:</p></ol>
426
427<h5>quantize_info</h5>
428<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
429
430<h5>images</h5>
431<ol><p>Specifies a pointer to a list of Image structures.</p></ol>
432
433 </div>
434<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
435_8c.html" target="source" name="RemapImage">RemapImage</a></h2>
436<div class="doc-section">
437
438<p>RemapImage() replaces the colors of an image with the closest color from a reference image.</p></ol>
439
440<p>The format of the RemapImage method is:</p>
441
442<pre class="code">
443 MagickBooleanType RemapImage(const QuantizeInfo *quantize_info,
444 Image *image,const Image *remap_image)
445</pre>
446
447<p>A description of each parameter follows:</p></ol>
448
449<h5>quantize_info</h5>
450<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
451
452<h5>image</h5>
453<ol><p>the image.</p></ol>
454
455<h5>remap_image</h5>
456<ol><p>the reference image.</p></ol>
457
458 </div>
459<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
460_8c.html" target="source" name="RemapImages">RemapImages</a></h2>
461<div class="doc-section">
462
463<p>RemapImages() replaces the colors of a sequence of images with the closest color from a reference image.</p></ol>
464
465<p>The format of the RemapImage method is:</p>
466
467<pre class="code">
468 MagickBooleanType RemapImages(const QuantizeInfo *quantize_info,
469 Image *images,Image *remap_image)
470</pre>
471
472<p>A description of each parameter follows:</p></ol>
473
474<h5>quantize_info</h5>
475<ol><p>Specifies a pointer to an QuantizeInfo structure.</p></ol>
476
477<h5>images</h5>
478<ol><p>the image sequence.</p></ol>
479
480<h5>remap_image</h5>
481<ol><p>the reference image.</p></ol>
482
483 </div>
484<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize
485_8c.html" target="source" name="SetGrayscaleImage">SetGrayscaleImage</a></h2>
486<div class="doc-section">
487
488<p>SetGrayscaleImage() converts an image to a PseudoClass grayscale image.</p></ol>
489
490<p>The format of the SetGrayscaleImage method is:</p>
491
492<pre class="code">
493 MagickBooleanType SetGrayscaleImage(Image *image)
494</pre>
495
496<p>A description of each parameter follows:</p></ol>
497
498<h5>image</h5>
499<ol><p>The image.</p></ol>
500
501 </div>
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