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216<div class="main">
217
cristy20398432011-08-11 01:31:50 +0000[diff] [blame]218<h1>Module quantize Methods</h1>
219<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>
cristy6f77f692011-02-15 15:31:39 +0000[diff] [blame]220
cristy20398432011-08-11 01:31:50 +0000[diff] [blame]221<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="QuantizeImage">QuantizeImage</a></h2>
222<div class="doc-section">
223
224<p>QuantizeImage() takes a standard RGB or monochrome images and quantizes them down to some fixed number of colors.</p>
225
226<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>
227
228<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>
229
230<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>
231
232<pre class="text">
233 the origin.
234</pre>
235
236<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>
237
238<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>
239
240<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>
241
242<p>A complete tree would require 19,173,961 nodes for k = 8, Cmax = 255.</p>
243<h5>avoid building a fully populated tree, QUANTIZE</h5>
244<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>
245
246<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>
247
248<pre class="text">
249 n1: Number of pixels whose color is contained in the RGB cube which
250 this node represents;
251</pre>
252
253<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>
254
255<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>
256
257<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>
258
259<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>
260
261<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>
262
263<p>This has the effect of minimizing any quantization error when merging two nodes together.</p>
264
265<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>
266
267<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>
268
269<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>
270
271<p>Assignment generates the output image from the pruned tree. The output</p>
272<h5>parts</h5>
273<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>
274
275<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>
276
277<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>
278
279<p>This method is based on a similar algorithm written by Paul Raveling.</p>
280
281 </div>
282<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="AcquireQuantizeInfo">AcquireQuantizeInfo</a></h2>
283<div class="doc-section">
284
285<p>AcquireQuantizeInfo() allocates the QuantizeInfo structure.</p>
286
287<p>The format of the AcquireQuantizeInfo method is:</p>
288
289<pre class="code">
290 QuantizeInfo *AcquireQuantizeInfo(const ImageInfo *image_info)
291</pre>
292
293<p>A description of each parameter follows:</p>
294
295<h5>image_info</h5>
296<p>the image info.</p>
297
298 </div>
299<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="CloneQuantizeInfo">CloneQuantizeInfo</a></h2>
300<div class="doc-section">
301
302<p>CloneQuantizeInfo() makes a duplicate of the given quantize info structure, or if quantize info is NULL, a new one.</p>
303
304<p>The format of the CloneQuantizeInfo method is:</p>
305
306<pre class="code">
307 QuantizeInfo *CloneQuantizeInfo(const QuantizeInfo *quantize_info)
308</pre>
309
310<p>A description of each parameter follows:</p>
311
312<h5>clone_info</h5>
313<p>Method CloneQuantizeInfo returns a duplicate of the given quantize info, or if image info is NULL a new one.</p>
314
315<h5>quantize_info</h5>
316<p>a structure of type info.</p>
317
318 </div>
319<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="CompressImageColormap">CompressImageColormap</a></h2>
320<div class="doc-section">
321
322<p>CompressImageColormap() compresses an image colormap by removing any duplicate or unused color entries.</p>
323
324<p>The format of the CompressImageColormap method is:</p>
325
326<pre class="code">
327 MagickBooleanType CompressImageColormap(Image *image)
328</pre>
329
330<p>A description of each parameter follows:</p>
331
332<h5>image</h5>
333<p>the image.</p>
334
335 </div>
336<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="DestroyQuantizeInfo">DestroyQuantizeInfo</a></h2>
337<div class="doc-section">
338
339<p>DestroyQuantizeInfo() deallocates memory associated with an QuantizeInfo structure.</p>
340
341<p>The format of the DestroyQuantizeInfo method is:</p>
342
343<pre class="code">
344 QuantizeInfo *DestroyQuantizeInfo(QuantizeInfo *quantize_info)
345</pre>
346
347<p>A description of each parameter follows:</p>
348
349<h5>quantize_info</h5>
350<p>Specifies a pointer to an QuantizeInfo structure.</p>
351
352 </div>
353<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="GetImageQuantizeError">GetImageQuantizeError</a></h2>
354<div class="doc-section">
355
356<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>
357
358<pre class="text">
359 o mean_error_per_pixel: This value is the mean error for any single
360 pixel in the image.
361</pre>
362
363<h5>normalized_mean_square_error</h5>
364<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>
365
366<h5>normalized_maximum_square_error</h5>
367<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>
368
369<p>The format of the GetImageQuantizeError method is:</p>
370
371<pre class="code">
372 MagickBooleanType GetImageQuantizeError(Image *image)
373</pre>
374
375<p>A description of each parameter follows.</p>
376
377<h5>image</h5>
378<p>the image.</p>
379
380 </div>
381<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="GetQuantizeInfo">GetQuantizeInfo</a></h2>
382<div class="doc-section">
383
384<p>GetQuantizeInfo() initializes the QuantizeInfo structure.</p>
385
386<p>The format of the GetQuantizeInfo method is:</p>
387
388<pre class="code">
389 GetQuantizeInfo(QuantizeInfo *quantize_info)
390</pre>
391
392<p>A description of each parameter follows:</p>
393
394<h5>quantize_info</h5>
395<p>Specifies a pointer to a QuantizeInfo structure.</p>
396
397 </div>
398<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="PosterizeImage">PosterizeImage</a></h2>
399<div class="doc-section">
400
401<p>PosterizeImage() reduces the image to a limited number of colors for a "poster" effect.</p>
402
403<p>The format of the PosterizeImage method is:</p>
404
405<pre class="code">
406 MagickBooleanType PosterizeImage(Image *image,const size_t levels,
407 const MagickBooleanType dither)
408 MagickBooleanType PosterizeImageChannel(Image *image,
409 const ChannelType channel,const size_t levels,
410 const MagickBooleanType dither)
411</pre>
412
413<p>A description of each parameter follows:</p>
414
415<h5>image</h5>
416<p>Specifies a pointer to an Image structure.</p>
417
418<h5>levels</h5>
419<p>Number of color levels allowed in each channel. Very low values (2, 3, or 4) have the most visible effect.</p>
420
421<h5>dither</h5>
422<p>Set this integer value to something other than zero to dither the mapped image.</p>
423
424 </div>
425<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="QuantizeImage">QuantizeImage</a></h2>
426<div class="doc-section">
427
428<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>
429
430<p>The format of the QuantizeImage method is:</p>
431
432<pre class="code">
433 MagickBooleanType QuantizeImage(const QuantizeInfo *quantize_info,
434 Image *image)
435</pre>
436
437<p>A description of each parameter follows:</p>
438
439<h5>quantize_info</h5>
440<p>Specifies a pointer to an QuantizeInfo structure.</p>
441
442<h5>image</h5>
443<p>the image.</p>
444
445 </div>
446<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="QuantizeImages">QuantizeImages</a></h2>
447<div class="doc-section">
448
449<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>
450
451<p>The format of the QuantizeImages method is:</p>
452
453<pre class="code">
454 MagickBooleanType QuantizeImages(const QuantizeInfo *quantize_info,
455 Image *images)
456</pre>
457
458<p>A description of each parameter follows:</p>
459
460<h5>quantize_info</h5>
461<p>Specifies a pointer to an QuantizeInfo structure.</p>
462
463<h5>images</h5>
464<p>Specifies a pointer to a list of Image structures.</p>
465
466 </div>
467<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="RemapImage">RemapImage</a></h2>
468<div class="doc-section">
469
470<p>RemapImage() replaces the colors of an image with the closest color from a reference image.</p>
471
472<p>The format of the RemapImage method is:</p>
473
474<pre class="code">
475 MagickBooleanType RemapImage(const QuantizeInfo *quantize_info,
476 Image *image,const Image *remap_image)
477</pre>
478
479<p>A description of each parameter follows:</p>
480
481<h5>quantize_info</h5>
482<p>Specifies a pointer to an QuantizeInfo structure.</p>
483
484<h5>image</h5>
485<p>the image.</p>
486
487<h5>remap_image</h5>
488<p>the reference image.</p>
489
490 </div>
491<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="RemapImages">RemapImages</a></h2>
492<div class="doc-section">
493
494<p>RemapImages() replaces the colors of a sequence of images with the closest color from a reference image.</p>
495
496<p>The format of the RemapImage method is:</p>
497
498<pre class="code">
499 MagickBooleanType RemapImages(const QuantizeInfo *quantize_info,
500 Image *images,Image *remap_image)
501</pre>
502
503<p>A description of each parameter follows:</p>
504
505<h5>quantize_info</h5>
506<p>Specifies a pointer to an QuantizeInfo structure.</p>
507
508<h5>images</h5>
509<p>the image sequence.</p>
510
511<h5>remap_image</h5>
512<p>the reference image.</p>
513
514 </div>
515<h2><a href="http://www.imagemagick.org/api/MagickCore/quantize_8c.html" id="SetGrayscaleImage">SetGrayscaleImage</a></h2>
516<div class="doc-section">
517
518<p>SetGrayscaleImage() converts an image to a PseudoClass grayscale image.</p>
519
520<p>The format of the SetGrayscaleImage method is:</p>
521
522<pre class="code">
523 MagickBooleanType SetGrayscaleImage(Image *image)
524</pre>
525
526<p>A description of each parameter follows:</p>
527
528<h5>image</h5>
529<p>The image.</p>
530
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