2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
6 % RRRR EEEEE SSSSS AAA M M PPPP L EEEEE %
7 % R R E SS A A MM MM P P L E %
8 % RRRR EEE SSS AAAAA M M M PPPP L EEE %
9 % R R E SS A A M M P L E %
10 % R R EEEEE SSSSS A A M M P LLLLL EEEEE %
13 % MagickCore Pixel Resampling Methods %
21 % Copyright 1999-2011 ImageMagick Studio LLC, a non-profit organization %
22 % dedicated to making software imaging solutions freely available. %
24 % You may not use this file except in compliance with the License. You may %
25 % obtain a copy of the License at %
27 % http://www.imagemagick.org/script/license.php %
29 % Unless required by applicable law or agreed to in writing, software %
30 % distributed under the License is distributed on an "AS IS" BASIS, %
31 % WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. %
32 % See the License for the specific language governing permissions and %
33 % limitations under the License. %
35 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
43 #include "MagickCore/studio.h"
44 #include "MagickCore/artifact.h"
45 #include "MagickCore/color-private.h"
46 #include "MagickCore/cache.h"
47 #include "MagickCore/draw.h"
48 #include "MagickCore/exception-private.h"
49 #include "MagickCore/gem.h"
50 #include "MagickCore/image.h"
51 #include "MagickCore/image-private.h"
52 #include "MagickCore/log.h"
53 #include "MagickCore/magick.h"
54 #include "MagickCore/memory_.h"
55 #include "MagickCore/pixel.h"
56 #include "MagickCore/pixel-accessor.h"
57 #include "MagickCore/quantum.h"
58 #include "MagickCore/random_.h"
59 #include "MagickCore/resample.h"
60 #include "MagickCore/resize.h"
61 #include "MagickCore/resize-private.h"
62 #include "MagickCore/transform.h"
63 #include "MagickCore/signature-private.h"
64 #include "MagickCore/utility.h"
65 #include "MagickCore/utility-private.h"
67 EWA Resampling Options
70 /* select ONE resampling method */
71 #define EWA 1 /* Normal EWA handling - raw or clamped */
72 /* if 0 then use "High Quality EWA" */
73 #define EWA_CLAMP 1 /* EWA Clamping from Nicolas Robidoux */
75 #define FILTER_LUT 1 /* Use a LUT rather then direct filter calls */
77 /* output debugging information */
78 #define DEBUG_ELLIPSE 0 /* output ellipse info for debug */
79 #define DEBUG_HIT_MISS 0 /* output hit/miss pixels (as gnuplot commands) */
80 #define DEBUG_NO_PIXEL_HIT 0 /* Make pixels that fail to hit anything - RED */
83 #define WLUT_WIDTH 1024 /* size of the filter cache */
89 struct _ResampleFilter
103 /* Information about image being resampled */
107 PixelInterpolateMethod
116 /* processing settings needed */
125 /* current ellipitical area being resampled around center point */
128 Vlimit, Ulimit, Uwidth, slope;
131 /* LUT of weights for filtered average in elliptical area */
133 filter_lut[WLUT_WIDTH];
135 /* Use a Direct call to the filter functions */
143 /* the practical working support of the filter */
152 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
156 % A c q u i r e R e s a m p l e I n f o %
160 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
162 % AcquireResampleFilter() initializes the information resample needs do to a
163 % scaled lookup of a color from an image, using area sampling.
165 % The algorithm is based on a Elliptical Weighted Average, where the pixels
166 % found in a large elliptical area is averaged together according to a
167 % weighting (filter) function. For more details see "Fundamentals of Texture
168 % Mapping and Image Warping" a master's thesis by Paul.S.Heckbert, June 17,
169 % 1989. Available for free from, http://www.cs.cmu.edu/~ph/
171 % As EWA resampling (or any sort of resampling) can require a lot of
172 % calculations to produce a distorted scaling of the source image for each
173 % output pixel, the ResampleFilter structure generated holds that information
174 % between individual image resampling.
176 % This function will make the appropriate AcquireCacheView() calls
177 % to view the image, calling functions do not need to open a cache view.
180 % resample_filter=AcquireResampleFilter(image,exception);
181 % SetResampleFilter(resample_filter, GaussianFilter, 1.0);
182 % for (y=0; y < (ssize_t) image->rows; y++) {
183 % for (x=0; x < (ssize_t) image->columns; x++) {
185 % ScaleResampleFilter(resample_filter, ... scaling vectors ...);
186 % (void) ResamplePixelColor(resample_filter,u,v,&pixel);
187 % ... assign resampled pixel value ...
190 % DestroyResampleFilter(resample_filter);
192 % The format of the AcquireResampleFilter method is:
194 % ResampleFilter *AcquireResampleFilter(const Image *image,
195 % ExceptionInfo *exception)
197 % A description of each parameter follows:
199 % o image: the image.
201 % o exception: return any errors or warnings in this structure.
204 MagickExport ResampleFilter *AcquireResampleFilter(const Image *image,
205 ExceptionInfo *exception)
207 register ResampleFilter
210 assert(image != (Image *) NULL);
211 assert(image->signature == MagickSignature);
212 if (image->debug != MagickFalse)
213 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
214 assert(exception != (ExceptionInfo *) NULL);
215 assert(exception->signature == MagickSignature);
217 resample_filter=(ResampleFilter *) AcquireMagickMemory(
218 sizeof(*resample_filter));
219 if (resample_filter == (ResampleFilter *) NULL)
220 ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
221 (void) ResetMagickMemory(resample_filter,0,sizeof(*resample_filter));
223 resample_filter->exception=exception;
224 resample_filter->image=ReferenceImage((Image *) image);
225 resample_filter->view=AcquireCacheView(resample_filter->image);
227 resample_filter->debug=IsEventLogging();
228 resample_filter->signature=MagickSignature;
230 resample_filter->image_area=(ssize_t) (image->columns*image->rows);
231 resample_filter->average_defined = MagickFalse;
233 /* initialise the resampling filter settings */
234 SetResampleFilter(resample_filter, image->filter, image->blur);
235 (void) SetResampleFilterInterpolateMethod(resample_filter,
237 (void) SetResampleFilterVirtualPixelMethod(resample_filter,
238 GetImageVirtualPixelMethod(image));
240 return(resample_filter);
244 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
248 % D e s t r o y R e s a m p l e I n f o %
252 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
254 % DestroyResampleFilter() finalizes and cleans up the resampling
255 % resample_filter as returned by AcquireResampleFilter(), freeing any memory
256 % or other information as needed.
258 % The format of the DestroyResampleFilter method is:
260 % ResampleFilter *DestroyResampleFilter(ResampleFilter *resample_filter)
262 % A description of each parameter follows:
264 % o resample_filter: resampling information structure
267 MagickExport ResampleFilter *DestroyResampleFilter(
268 ResampleFilter *resample_filter)
270 assert(resample_filter != (ResampleFilter *) NULL);
271 assert(resample_filter->signature == MagickSignature);
272 assert(resample_filter->image != (Image *) NULL);
273 if (resample_filter->debug != MagickFalse)
274 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
275 resample_filter->image->filename);
276 resample_filter->view=DestroyCacheView(resample_filter->view);
277 resample_filter->image=DestroyImage(resample_filter->image);
279 resample_filter->filter_def=DestroyResizeFilter(resample_filter->filter_def);
281 resample_filter->signature=(~MagickSignature);
282 resample_filter=(ResampleFilter *) RelinquishMagickMemory(resample_filter);
283 return(resample_filter);
287 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
291 % R e s a m p l e P i x e l C o l o r %
295 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
297 % ResamplePixelColor() samples the pixel values surrounding the location
298 % given using an elliptical weighted average, at the scale previously
299 % calculated, and in the most efficent manner possible for the
300 % VirtualPixelMethod setting.
302 % The format of the ResamplePixelColor method is:
304 % MagickBooleanType ResamplePixelColor(ResampleFilter *resample_filter,
305 % const double u0,const double v0,PixelInfo *pixel)
307 % A description of each parameter follows:
309 % o resample_filter: the resample filter.
311 % o u0,v0: A double representing the center of the area to resample,
312 % The distortion transformed transformed x,y coordinate.
314 % o pixel: the resampled pixel is returned here.
317 MagickExport MagickBooleanType ResamplePixelColor(
318 ResampleFilter *resample_filter,const double u0,const double v0,
324 ssize_t u,v, v1, v2, uw, hit;
327 double divisor_c,divisor_m;
328 register double weight;
329 register const Quantum *pixels;
330 assert(resample_filter != (ResampleFilter *) NULL);
331 assert(resample_filter->signature == MagickSignature);
334 /* GetPixelInfo(resample_filter->image,pixel); */
335 if ( resample_filter->do_interpolate ) {
336 status=InterpolatePixelInfo(resample_filter->image,
337 resample_filter->view,resample_filter->interpolate,u0,v0,pixel,
338 resample_filter->exception);
343 (void) FormatLocaleFile(stderr, "u0=%lf; v0=%lf;\n", u0, v0);
347 Does resample area Miss the image?
348 And is that area a simple solid color - then return that color
351 switch ( resample_filter->virtual_pixel ) {
352 case BackgroundVirtualPixelMethod:
353 case TransparentVirtualPixelMethod:
354 case BlackVirtualPixelMethod:
355 case GrayVirtualPixelMethod:
356 case WhiteVirtualPixelMethod:
357 case MaskVirtualPixelMethod:
358 if ( resample_filter->limit_reached
359 || u0 + resample_filter->Ulimit < 0.0
360 || u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
361 || v0 + resample_filter->Vlimit < 0.0
362 || v0 - resample_filter->Vlimit > (double) resample_filter->image->rows
367 case UndefinedVirtualPixelMethod:
368 case EdgeVirtualPixelMethod:
369 if ( ( u0 + resample_filter->Ulimit < 0.0 && v0 + resample_filter->Vlimit < 0.0 )
370 || ( u0 + resample_filter->Ulimit < 0.0
371 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows )
372 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
373 && v0 + resample_filter->Vlimit < 0.0 )
374 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
375 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows )
379 case HorizontalTileVirtualPixelMethod:
380 if ( v0 + resample_filter->Vlimit < 0.0
381 || v0 - resample_filter->Vlimit > (double) resample_filter->image->rows
383 hit++; /* outside the horizontally tiled images. */
385 case VerticalTileVirtualPixelMethod:
386 if ( u0 + resample_filter->Ulimit < 0.0
387 || u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
389 hit++; /* outside the vertically tiled images. */
391 case DitherVirtualPixelMethod:
392 if ( ( u0 + resample_filter->Ulimit < -32.0 && v0 + resample_filter->Vlimit < -32.0 )
393 || ( u0 + resample_filter->Ulimit < -32.0
394 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+32.0 )
395 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+32.0
396 && v0 + resample_filter->Vlimit < -32.0 )
397 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+32.0
398 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+32.0 )
402 case TileVirtualPixelMethod:
403 case MirrorVirtualPixelMethod:
404 case RandomVirtualPixelMethod:
405 case HorizontalTileEdgeVirtualPixelMethod:
406 case VerticalTileEdgeVirtualPixelMethod:
407 case CheckerTileVirtualPixelMethod:
408 /* resampling of area is always needed - no VP limits */
412 /* whole area is a solid color -- just return that color */
413 status=InterpolatePixelInfo(resample_filter->image,
414 resample_filter->view,IntegerInterpolatePixel,u0,v0,pixel,
415 resample_filter->exception);
420 Scaling limits reached, return an 'averaged' result.
422 if ( resample_filter->limit_reached ) {
423 switch ( resample_filter->virtual_pixel ) {
424 /* This is always handled by the above, so no need.
425 case BackgroundVirtualPixelMethod:
426 case ConstantVirtualPixelMethod:
427 case TransparentVirtualPixelMethod:
428 case GrayVirtualPixelMethod,
429 case WhiteVirtualPixelMethod
430 case MaskVirtualPixelMethod:
432 case UndefinedVirtualPixelMethod:
433 case EdgeVirtualPixelMethod:
434 case DitherVirtualPixelMethod:
435 case HorizontalTileEdgeVirtualPixelMethod:
436 case VerticalTileEdgeVirtualPixelMethod:
437 /* We need an average edge pixel, from the correct edge!
438 How should I calculate an average edge color?
439 Just returning an averaged neighbourhood,
440 works well in general, but falls down for TileEdge methods.
441 This needs to be done properly!!!!!!
443 status=InterpolatePixelInfo(resample_filter->image,
444 resample_filter->view,AverageInterpolatePixel,u0,v0,pixel,
445 resample_filter->exception);
447 case HorizontalTileVirtualPixelMethod:
448 case VerticalTileVirtualPixelMethod:
449 /* just return the background pixel - Is there more direct way? */
450 status=InterpolatePixelInfo(resample_filter->image,
451 resample_filter->view,IntegerInterpolatePixel,-1.0,-1.0,pixel,
452 resample_filter->exception);
454 case TileVirtualPixelMethod:
455 case MirrorVirtualPixelMethod:
456 case RandomVirtualPixelMethod:
457 case CheckerTileVirtualPixelMethod:
459 /* generate a average color of the WHOLE image */
460 if ( resample_filter->average_defined == MagickFalse ) {
467 GetPixelInfo(resample_filter->image,(PixelInfo *)
468 &resample_filter->average_pixel);
469 resample_filter->average_defined=MagickTrue;
471 /* Try to get an averaged pixel color of whole image */
472 average_image=ResizeImage(resample_filter->image,1,1,BoxFilter,1.0,
473 resample_filter->exception);
474 if (average_image == (Image *) NULL)
476 *pixel=resample_filter->average_pixel; /* FAILED */
479 average_view=AcquireCacheView(average_image);
480 pixels=GetCacheViewVirtualPixels(average_view,0,0,1,1,
481 resample_filter->exception);
482 if (pixels == (const Quantum *) NULL) {
483 average_view=DestroyCacheView(average_view);
484 average_image=DestroyImage(average_image);
485 *pixel=resample_filter->average_pixel; /* FAILED */
488 SetPixelInfo(resample_filter->image,pixels,
489 &(resample_filter->average_pixel));
490 average_view=DestroyCacheView(average_view);
491 average_image=DestroyImage(average_image);
493 if ( resample_filter->virtual_pixel == CheckerTileVirtualPixelMethod )
495 /* CheckerTile is avergae of image average half background */
496 /* FUTURE: replace with a 50% blend of both pixels */
498 weight = QuantumScale*((MagickRealType)
499 resample_filter->average_pixel.alpha);
500 resample_filter->average_pixel.red *= weight;
501 resample_filter->average_pixel.green *= weight;
502 resample_filter->average_pixel.blue *= weight;
505 weight = QuantumScale*((MagickRealType)
506 resample_filter->image->background_color.alpha);
507 resample_filter->average_pixel.red +=
508 weight*resample_filter->image->background_color.red;
509 resample_filter->average_pixel.green +=
510 weight*resample_filter->image->background_color.green;
511 resample_filter->average_pixel.blue +=
512 weight*resample_filter->image->background_color.blue;
513 resample_filter->average_pixel.alpha +=
514 resample_filter->image->background_color.alpha;
517 resample_filter->average_pixel.red /= divisor_c;
518 resample_filter->average_pixel.green /= divisor_c;
519 resample_filter->average_pixel.blue /= divisor_c;
520 resample_filter->average_pixel.alpha /= 2;
524 *pixel=resample_filter->average_pixel;
531 Initialize weighted average data collection
536 pixel->red = pixel->green = pixel->blue = 0.0;
537 if (pixel->colorspace == CMYKColorspace)
539 if (pixel->matte != MagickFalse)
543 Determine the parellelogram bounding box fitted to the ellipse
544 centered at u0,v0. This area is bounding by the lines...
546 v1 = (ssize_t)ceil(v0 - resample_filter->Vlimit); /* range of scan lines */
547 v2 = (ssize_t)floor(v0 + resample_filter->Vlimit);
549 /* scan line start and width accross the parallelogram */
550 u1 = u0 + (v1-v0)*resample_filter->slope - resample_filter->Uwidth;
551 uw = (ssize_t)(2.0*resample_filter->Uwidth)+1;
554 (void) FormatLocaleFile(stderr, "v1=%ld; v2=%ld\n", (long)v1, (long)v2);
555 (void) FormatLocaleFile(stderr, "u1=%ld; uw=%ld\n", (long)u1, (long)uw);
557 # define DEBUG_HIT_MISS 0 /* only valid if DEBUG_ELLIPSE is enabled */
561 Do weighted resampling of all pixels, within the scaled ellipse,
562 bound by a Parellelogram fitted to the ellipse.
564 DDQ = 2*resample_filter->A;
565 for( v=v1; v<=v2; v++ ) {
567 long uu = ceil(u1); /* actual pixel location (for debug only) */
568 (void) FormatLocaleFile(stderr, "# scan line from pixel %ld, %ld\n", (long)uu, (long)v);
570 u = (ssize_t)ceil(u1); /* first pixel in scanline */
571 u1 += resample_filter->slope; /* start of next scan line */
574 /* location of this first pixel, relative to u0,v0 */
578 /* Q = ellipse quotent ( if Q<F then pixel is inside ellipse) */
579 Q = (resample_filter->A*U + resample_filter->B*V)*U + resample_filter->C*V*V;
580 DQ = resample_filter->A*(2.0*U+1) + resample_filter->B*V;
582 /* get the scanline of pixels for this v */
583 pixels=GetCacheViewVirtualPixels(resample_filter->view,u,v,(size_t) uw,
584 1,resample_filter->exception);
585 if (pixels == (const Quantum *) NULL)
588 /* count up the weighted pixel colors */
589 for( u=0; u<uw; u++ ) {
591 /* Note that the ellipse has been pre-scaled so F = WLUT_WIDTH */
592 if ( Q < (double)WLUT_WIDTH ) {
593 weight = resample_filter->filter_lut[(int)Q];
595 /* Note that the ellipse has been pre-scaled so F = support^2 */
596 if ( Q < (double)resample_filter->F ) {
597 weight = GetResizeFilterWeight(resample_filter->filter_def,
598 sqrt(Q)); /* a SquareRoot! Arrggghhhhh... */
601 pixel->alpha += weight*GetPixelAlpha(resample_filter->image,pixels);
604 if (pixel->matte != MagickFalse)
605 weight *= QuantumScale*((MagickRealType) GetPixelAlpha(resample_filter->image,pixels));
606 pixel->red += weight*GetPixelRed(resample_filter->image,pixels);
607 pixel->green += weight*GetPixelGreen(resample_filter->image,pixels);
608 pixel->blue += weight*GetPixelBlue(resample_filter->image,pixels);
609 if (pixel->colorspace == CMYKColorspace)
610 pixel->black += weight*GetPixelBlack(resample_filter->image,pixels);
615 /* mark the pixel according to hit/miss of the ellipse */
616 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 3\n",
617 (long)uu-.1,(double)v-.1,(long)uu+.1,(long)v+.1);
618 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 3\n",
619 (long)uu+.1,(double)v-.1,(long)uu-.1,(long)v+.1);
621 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 1\n",
622 (long)uu-.1,(double)v-.1,(long)uu+.1,(long)v+.1);
623 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 1\n",
624 (long)uu+.1,(double)v-.1,(long)uu-.1,(long)v+.1);
630 pixels+=GetPixelChannels(resample_filter->image);
636 (void) FormatLocaleFile(stderr, "Hit=%ld; Total=%ld;\n", (long)hit, (long)uw*(v2-v1) );
640 Result sanity check -- this should NOT happen
643 /* not enough pixels in resampling, resort to direct interpolation */
644 #if DEBUG_NO_PIXEL_HIT
645 pixel->alpha = pixel->red = pixel->green = pixel->blue = 0;
646 pixel->red = QuantumRange; /* show pixels for which EWA fails */
648 status=InterpolatePixelInfo(resample_filter->image,
649 resample_filter->view,resample_filter->interpolate,u0,v0,pixel,
650 resample_filter->exception);
656 Finialize results of resampling
658 divisor_m = 1.0/divisor_m;
659 pixel->alpha = (MagickRealType) ClampToQuantum(divisor_m*pixel->alpha);
660 divisor_c = 1.0/divisor_c;
661 pixel->red = (MagickRealType) ClampToQuantum(divisor_c*pixel->red);
662 pixel->green = (MagickRealType) ClampToQuantum(divisor_c*pixel->green);
663 pixel->blue = (MagickRealType) ClampToQuantum(divisor_c*pixel->blue);
664 if (pixel->colorspace == CMYKColorspace)
665 pixel->black = (MagickRealType) ClampToQuantum(divisor_c*pixel->black);
671 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
675 - C l a m p U p A x e s %
679 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
681 % ClampUpAxes() function converts the input vectors into a major and
682 % minor axis unit vectors, and their magnitude. This allows us to
683 % ensure that the ellipse generated is never smaller than the unit
684 % circle and thus never too small for use in EWA resampling.
686 % This purely mathematical 'magic' was provided by Professor Nicolas
687 % Robidoux and his Masters student Chantal Racette.
689 % Reference: "We Recommend Singular Value Decomposition", David Austin
690 % http://www.ams.org/samplings/feature-column/fcarc-svd
692 % By generating major and minor axis vectors, we can actually use the
693 % ellipse in its "canonical form", by remapping the dx,dy of the
694 % sampled point into distances along the major and minor axis unit
697 % Reference: http://en.wikipedia.org/wiki/Ellipse#Canonical_form
699 static inline void ClampUpAxes(const double dux,
705 double *major_unit_x,
706 double *major_unit_y,
707 double *minor_unit_x,
708 double *minor_unit_y)
711 * ClampUpAxes takes an input 2x2 matrix
713 * [ a b ] = [ dux duy ]
714 * [ c d ] = [ dvx dvy ]
716 * and computes from it the major and minor axis vectors [major_x,
717 * major_y] and [minor_x,minor_y] of the smallest ellipse containing
718 * both the unit disk and the ellipse which is the image of the unit
719 * disk by the linear transformation
721 * [ dux duy ] [S] = [s]
722 * [ dvx dvy ] [T] = [t]
724 * (The vector [S,T] is the difference between a position in output
725 * space and [X,Y]; the vector [s,t] is the difference between a
726 * position in input space and [x,y].)
731 * major_mag is the half-length of the major axis of the "new"
734 * minor_mag is the half-length of the minor axis of the "new"
737 * major_unit_x is the x-coordinate of the major axis direction vector
738 * of both the "old" and "new" ellipses.
740 * major_unit_y is the y-coordinate of the major axis direction vector.
742 * minor_unit_x is the x-coordinate of the minor axis direction vector.
744 * minor_unit_y is the y-coordinate of the minor axis direction vector.
746 * Unit vectors are useful for computing projections, in particular,
747 * to compute the distance between a point in output space and the
748 * center of a unit disk in output space, using the position of the
749 * corresponding point [s,t] in input space. Following the clamping,
750 * the square of this distance is
752 * ( ( s * major_unit_x + t * major_unit_y ) / major_mag )^2
754 * ( ( s * minor_unit_x + t * minor_unit_y ) / minor_mag )^2
756 * If such distances will be computed for many [s,t]'s, it makes
757 * sense to actually compute the reciprocal of major_mag and
758 * minor_mag and multiply them by the above unit lengths.
760 * Now, if you want to modify the input pair of tangent vectors so
761 * that it defines the modified ellipse, all you have to do is set
763 * newdux = major_mag * major_unit_x
764 * newdvx = major_mag * major_unit_y
765 * newduy = minor_mag * minor_unit_x = minor_mag * -major_unit_y
766 * newdvy = minor_mag * minor_unit_y = minor_mag * major_unit_x
768 * and use these tangent vectors as if they were the original ones.
769 * Usually, this is a drastic change in the tangent vectors even if
770 * the singular values are not clamped; for example, the minor axis
771 * vector always points in a direction which is 90 degrees
772 * counterclockwise from the direction of the major axis vector.
777 * GOAL: Fix things so that the pullback, in input space, of a disk
778 * of radius r in output space is an ellipse which contains, at
779 * least, a disc of radius r. (Make this hold for any r>0.)
781 * ESSENCE OF THE METHOD: Compute the product of the first two
782 * factors of an SVD of the linear transformation defining the
783 * ellipse and make sure that both its columns have norm at least 1.
784 * Because rotations and reflexions map disks to themselves, it is
785 * not necessary to compute the third (rightmost) factor of the SVD.
787 * DETAILS: Find the singular values and (unit) left singular
788 * vectors of Jinv, clampling up the singular values to 1, and
789 * multiply the unit left singular vectors by the new singular
790 * values in order to get the minor and major ellipse axis vectors.
792 * Image resampling context:
794 * The Jacobian matrix of the transformation at the output point
795 * under consideration is defined as follows:
797 * Consider the transformation (x,y) -> (X,Y) from input locations
798 * to output locations. (Anthony Thyssen, elsewhere in resample.c,
799 * uses the notation (u,v) -> (x,y).)
801 * The Jacobian matrix of the transformation at (x,y) is equal to
803 * J = [ A, B ] = [ dX/dx, dX/dy ]
804 * [ C, D ] [ dY/dx, dY/dy ]
806 * that is, the vector [A,C] is the tangent vector corresponding to
807 * input changes in the horizontal direction, and the vector [B,D]
808 * is the tangent vector corresponding to input changes in the
809 * vertical direction.
811 * In the context of resampling, it is natural to use the inverse
812 * Jacobian matrix Jinv because resampling is generally performed by
813 * pulling pixel locations in the output image back to locations in
814 * the input image. Jinv is
816 * Jinv = [ a, b ] = [ dx/dX, dx/dY ]
817 * [ c, d ] [ dy/dX, dy/dY ]
819 * Note: Jinv can be computed from J with the following matrix
822 * Jinv = 1/(A*D-B*C) [ D, -B ]
825 * What we do is modify Jinv so that it generates an ellipse which
826 * is as close as possible to the original but which contains the
827 * unit disk. This can be accomplished as follows:
833 * be an SVD decomposition of Jinv. (The SVD is not unique, but the
834 * final ellipse does not depend on the particular SVD.)
836 * We could clamp up the entries of the diagonal matrix Sigma so
837 * that they are at least 1, and then set
839 * Jinv = U newSigma V^T.
841 * However, we do not need to compute V for the following reason:
842 * V^T is an orthogonal matrix (that is, it represents a combination
843 * of rotations and reflexions) so that it maps the unit circle to
844 * itself. For this reason, the exact value of V does not affect the
845 * final ellipse, and we can choose V to be the identity
850 * In the end, we return the two diagonal entries of newSigma
851 * together with the two columns of U.
854 * ClampUpAxes was written by Nicolas Robidoux and Chantal Racette
855 * of Laurentian University with insightful suggestions from Anthony
856 * Thyssen and funding from the National Science and Engineering
857 * Research Council of Canada. It is distinguished from its
858 * predecessors by its efficient handling of degenerate cases.
860 * The idea of clamping up the EWA ellipse's major and minor axes so
861 * that the result contains the reconstruction kernel filter support
862 * is taken from Andreas Gustaffson's Masters thesis "Interactive
863 * Image Warping", Helsinki University of Technology, Faculty of
864 * Information Technology, 59 pages, 1993 (see Section 3.6).
866 * The use of the SVD to clamp up the singular values of the
867 * Jacobian matrix of the pullback transformation for EWA resampling
868 * is taken from the astrophysicist Craig DeForest. It is
869 * implemented in his PDL::Transform code (PDL = Perl Data
872 const double a = dux;
873 const double b = duy;
874 const double c = dvx;
875 const double d = dvy;
877 * n is the matrix Jinv * transpose(Jinv). Eigenvalues of n are the
878 * squares of the singular values of Jinv.
880 const double aa = a*a;
881 const double bb = b*b;
882 const double cc = c*c;
883 const double dd = d*d;
885 * Eigenvectors of n are left singular vectors of Jinv.
887 const double n11 = aa+bb;
888 const double n12 = a*c+b*d;
889 const double n21 = n12;
890 const double n22 = cc+dd;
891 const double det = a*d-b*c;
892 const double twice_det = det+det;
893 const double frobenius_squared = n11+n22;
894 const double discriminant =
895 (frobenius_squared+twice_det)*(frobenius_squared-twice_det);
896 const double sqrt_discriminant = sqrt(discriminant);
898 * s1 is the largest singular value of the inverse Jacobian
899 * matrix. In other words, its reciprocal is the smallest singular
900 * value of the Jacobian matrix itself.
901 * If s1 = 0, both singular values are 0, and any orthogonal pair of
902 * left and right factors produces a singular decomposition of Jinv.
905 * Initially, we only compute the squares of the singular values.
907 const double s1s1 = 0.5*(frobenius_squared+sqrt_discriminant);
909 * s2 the smallest singular value of the inverse Jacobian
910 * matrix. Its reciprocal is the largest singular value of the
911 * Jacobian matrix itself.
913 const double s2s2 = 0.5*(frobenius_squared-sqrt_discriminant);
914 const double s1s1minusn11 = s1s1-n11;
915 const double s1s1minusn22 = s1s1-n22;
917 * u1, the first column of the U factor of a singular decomposition
918 * of Jinv, is a (non-normalized) left singular vector corresponding
919 * to s1. It has entries u11 and u21. We compute u1 from the fact
920 * that it is an eigenvector of n corresponding to the eigenvalue
923 const double s1s1minusn11_squared = s1s1minusn11*s1s1minusn11;
924 const double s1s1minusn22_squared = s1s1minusn22*s1s1minusn22;
926 * The following selects the largest row of n-s1^2 I as the one
927 * which is used to find the eigenvector. If both s1^2-n11 and
928 * s1^2-n22 are zero, n-s1^2 I is the zero matrix. In that case,
929 * any vector is an eigenvector; in addition, norm below is equal to
930 * zero, and, in exact arithmetic, this is the only case in which
931 * norm = 0. So, setting u1 to the simple but arbitrary vector [1,0]
932 * if norm = 0 safely takes care of all cases.
934 const double temp_u11 =
935 ( (s1s1minusn11_squared>=s1s1minusn22_squared) ? n12 : s1s1minusn22 );
936 const double temp_u21 =
937 ( (s1s1minusn11_squared>=s1s1minusn22_squared) ? s1s1minusn11 : n21 );
938 const double norm = sqrt(temp_u11*temp_u11+temp_u21*temp_u21);
940 * Finalize the entries of first left singular vector (associated
941 * with the largest singular value).
943 const double u11 = ( (norm>0.0) ? temp_u11/norm : 1.0 );
944 const double u21 = ( (norm>0.0) ? temp_u21/norm : 0.0 );
946 * Clamp the singular values up to 1.
948 *major_mag = ( (s1s1<=1.0) ? 1.0 : sqrt(s1s1) );
949 *minor_mag = ( (s2s2<=1.0) ? 1.0 : sqrt(s2s2) );
951 * Return the unit major and minor axis direction vectors.
955 *minor_unit_x = -u21;
961 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
965 % S c a l e R e s a m p l e F i l t e r %
969 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
971 % ScaleResampleFilter() does all the calculations needed to resample an image
972 % at a specific scale, defined by two scaling vectors. This not using
973 % a orthogonal scaling, but two distorted scaling vectors, to allow the
974 % generation of a angled ellipse.
976 % As only two deritive scaling vectors are used the center of the ellipse
977 % must be the center of the lookup. That is any curvature that the
978 % distortion may produce is discounted.
980 % The input vectors are produced by either finding the derivitives of the
981 % distortion function, or the partial derivitives from a distortion mapping.
982 % They do not need to be the orthogonal dx,dy scaling vectors, but can be
983 % calculated from other derivatives. For example you could use dr,da/r
984 % polar coordinate vector scaling vectors
986 % If u,v = DistortEquation(x,y) OR u = Fu(x,y); v = Fv(x,y)
987 % Then the scaling vectors are determined from the deritives...
988 % du/dx, dv/dx and du/dy, dv/dy
989 % If the resulting scaling vectors is othogonally aligned then...
990 % dv/dx = 0 and du/dy = 0
991 % Producing an othogonally alligned ellipse in source space for the area to
994 % Note that scaling vectors are different to argument order. Argument order
995 % is the general order the deritives are extracted from the distortion
996 % equations, and not the scaling vectors. As such the middle two vaules
997 % may be swapped from what you expect. Caution is advised.
999 % WARNING: It is assumed that any SetResampleFilter() method call will
1000 % always be performed before the ScaleResampleFilter() method, so that the
1001 % size of the ellipse will match the support for the resampling filter being
1004 % The format of the ScaleResampleFilter method is:
1006 % void ScaleResampleFilter(const ResampleFilter *resample_filter,
1007 % const double dux,const double duy,const double dvx,const double dvy)
1009 % A description of each parameter follows:
1011 % o resample_filter: the resampling resample_filterrmation defining the
1012 % image being resampled
1014 % o dux,duy,dvx,dvy:
1015 % The deritives or scaling vectors defining the EWA ellipse.
1016 % NOTE: watch the order, which is based on the order deritives
1017 % are usally determined from distortion equations (see above).
1018 % The middle two values may need to be swapped if you are thinking
1019 % in terms of scaling vectors.
1022 MagickExport void ScaleResampleFilter(ResampleFilter *resample_filter,
1023 const double dux,const double duy,const double dvx,const double dvy)
1027 assert(resample_filter != (ResampleFilter *) NULL);
1028 assert(resample_filter->signature == MagickSignature);
1030 resample_filter->limit_reached = MagickFalse;
1032 /* A 'point' filter forces use of interpolation instead of area sampling */
1033 if ( resample_filter->filter == PointFilter )
1034 return; /* EWA turned off - nothing to do */
1037 (void) FormatLocaleFile(stderr, "# -----\n" );
1038 (void) FormatLocaleFile(stderr, "dux=%lf; dvx=%lf; duy=%lf; dvy=%lf;\n",
1039 dux, dvx, duy, dvy);
1042 /* Find Ellipse Coefficents such that
1043 A*u^2 + B*u*v + C*v^2 = F
1044 With u,v relative to point around which we are resampling.
1045 And the given scaling dx,dy vectors in u,v space
1046 du/dx,dv/dx and du/dy,dv/dy
1049 /* Direct conversion of derivatives into elliptical coefficients
1050 However when magnifying images, the scaling vectors will be small
1051 resulting in a ellipse that is too small to sample properly.
1052 As such we need to clamp the major/minor axis to a minumum of 1.0
1053 to prevent it getting too small.
1063 ClampUpAxes(dux,dvx,duy,dvy, &major_mag, &minor_mag,
1064 &major_x, &major_y, &minor_x, &minor_y);
1065 major_x *= major_mag; major_y *= major_mag;
1066 minor_x *= minor_mag; minor_y *= minor_mag;
1068 (void) FormatLocaleFile(stderr, "major_x=%lf; major_y=%lf; minor_x=%lf; minor_y=%lf;\n",
1069 major_x, major_y, minor_x, minor_y);
1071 A = major_y*major_y+minor_y*minor_y;
1072 B = -2.0*(major_x*major_y+minor_x*minor_y);
1073 C = major_x*major_x+minor_x*minor_x;
1074 F = major_mag*minor_mag;
1075 F *= F; /* square it */
1077 #else /* raw unclamped EWA */
1078 A = dvx*dvx+dvy*dvy;
1079 B = -2.0*(dux*dvx+duy*dvy);
1080 C = dux*dux+duy*duy;
1081 F = dux*dvy-duy*dvx;
1082 F *= F; /* square it */
1083 #endif /* EWA_CLAMP */
1087 This Paul Heckbert's "Higher Quality EWA" formula, from page 60 in his
1088 thesis, which adds a unit circle to the elliptical area so as to do both
1089 Reconstruction and Prefiltering of the pixels in the resampling. It also
1090 means it is always likely to have at least 4 pixels within the area of the
1091 ellipse, for weighted averaging. No scaling will result with F == 4.0 and
1092 a circle of radius 2.0, and F smaller than this means magnification is
1095 NOTE: This method produces a very blury result at near unity scale while
1096 producing perfect results for strong minitification and magnifications.
1098 However filter support is fixed to 2.0 (no good for Windowed Sinc filters)
1100 A = dvx*dvx+dvy*dvy+1;
1101 B = -2.0*(dux*dvx+duy*dvy);
1102 C = dux*dux+duy*duy+1;
1107 (void) FormatLocaleFile(stderr, "A=%lf; B=%lf; C=%lf; F=%lf\n", A,B,C,F);
1109 /* Figure out the various information directly about the ellipse.
1110 This information currently not needed at this time, but may be
1111 needed later for better limit determination.
1113 It is also good to have as a record for future debugging
1115 { double alpha, beta, gamma, Major, Minor;
1116 double Eccentricity, Ellipse_Area, Ellipse_Angle;
1120 gamma = sqrt(beta*beta + B*B );
1122 if ( alpha - gamma <= MagickEpsilon )
1125 Major = sqrt(2*F/(alpha - gamma));
1126 Minor = sqrt(2*F/(alpha + gamma));
1128 (void) FormatLocaleFile(stderr, "# Major=%lf; Minor=%lf\n", Major, Minor );
1130 /* other information about ellipse include... */
1131 Eccentricity = Major/Minor;
1132 Ellipse_Area = MagickPI*Major*Minor;
1133 Ellipse_Angle = atan2(B, A-C);
1135 (void) FormatLocaleFile(stderr, "# Angle=%lf Area=%lf\n",
1136 RadiansToDegrees(Ellipse_Angle), Ellipse_Area);
1140 /* If one or both of the scaling vectors is impossibly large
1141 (producing a very large raw F value), we may as well not bother
1142 doing any form of resampling since resampled area is very large.
1143 In this case some alternative means of pixel sampling, such as
1144 the average of the whole image is needed to get a reasonable
1145 result. Calculate only as needed.
1147 if ( (4*A*C - B*B) > MagickHuge ) {
1148 resample_filter->limit_reached = MagickTrue;
1152 /* Scale ellipse to match the filters support
1153 (that is, multiply F by the square of the support).
1155 F *= resample_filter->support;
1156 F *= resample_filter->support;
1158 /* Orthogonal bounds of the ellipse */
1159 resample_filter->Ulimit = sqrt(C*F/(A*C-0.25*B*B));
1160 resample_filter->Vlimit = sqrt(A*F/(A*C-0.25*B*B));
1162 /* Horizontally aligned parallelogram fitted to Ellipse */
1163 resample_filter->Uwidth = sqrt(F/A); /* Half of the parallelogram width */
1164 resample_filter->slope = -B/(2.0*A); /* Reciprocal slope of the parallelogram */
1167 (void) FormatLocaleFile(stderr, "Ulimit=%lf; Vlimit=%lf; UWidth=%lf; Slope=%lf;\n",
1168 resample_filter->Ulimit, resample_filter->Vlimit,
1169 resample_filter->Uwidth, resample_filter->slope );
1172 /* Check the absolute area of the parallelogram involved.
1173 * This limit needs more work, as it is too slow for larger images
1174 * with tiled views of the horizon.
1176 if ( (resample_filter->Uwidth * resample_filter->Vlimit)
1177 > (4.0*resample_filter->image_area)) {
1178 resample_filter->limit_reached = MagickTrue;
1182 /* Scale ellipse formula to directly index the Filter Lookup Table */
1183 { register double scale;
1185 /* scale so that F = WLUT_WIDTH; -- hardcoded */
1186 scale = (double)WLUT_WIDTH/F;
1188 /* scale so that F = resample_filter->F (support^2) */
1189 scale = resample_filter->F/F;
1191 resample_filter->A = A*scale;
1192 resample_filter->B = B*scale;
1193 resample_filter->C = C*scale;
1198 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1202 % S e t R e s a m p l e F i l t e r %
1206 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1208 % SetResampleFilter() set the resampling filter lookup table based on a
1209 % specific filter. Note that the filter is used as a radial filter not as a
1210 % two pass othogonally aligned resampling filter.
1212 % The default Filter, is Gaussian, which is the standard filter used by the
1213 % original paper on the Elliptical Weighted Everage Algorithm. However other
1214 % filters can also be used.
1216 % The format of the SetResampleFilter method is:
1218 % void SetResampleFilter(ResampleFilter *resample_filter,
1219 % const FilterTypes filter,const double blur)
1221 % A description of each parameter follows:
1223 % o resample_filter: resampling resample_filterrmation structure
1225 % o filter: the resize filter for elliptical weighting LUT
1227 % o blur: filter blur factor (radial scaling) for elliptical weighting LUT
1230 MagickExport void SetResampleFilter(ResampleFilter *resample_filter,
1231 const FilterTypes filter,const double blur)
1236 assert(resample_filter != (ResampleFilter *) NULL);
1237 assert(resample_filter->signature == MagickSignature);
1239 resample_filter->do_interpolate = MagickFalse;
1240 resample_filter->filter = filter;
1242 if ( filter == PointFilter )
1244 resample_filter->do_interpolate = MagickTrue;
1245 return; /* EWA turned off - nothing more to do */
1248 /* Set a default cylindrical filter of a 'low blur' Jinc windowed Jinc */
1249 if ( filter == UndefinedFilter )
1250 resample_filter->filter = RobidouxFilter;
1252 resize_filter = AcquireResizeFilter(resample_filter->image,
1253 resample_filter->filter,blur,MagickTrue,resample_filter->exception);
1254 if (resize_filter == (ResizeFilter *) NULL)
1256 (void) ThrowMagickException(resample_filter->exception,GetMagickModule(),
1257 ModuleError, "UnableToSetFilteringValue",
1258 "Fall back to default EWA gaussian filter");
1259 resample_filter->filter = PointFilter;
1262 /* Get the practical working support for the filter,
1263 * after any API call blur factors have been accoded for.
1266 resample_filter->support = GetResizeFilterSupport(resize_filter);
1268 resample_filter->support = 2.0; /* fixed support size for HQ-EWA */
1272 /* Fill the LUT with the weights from the selected filter function */
1277 /* Scale radius so the filter LUT covers the full support range */
1278 r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
1279 for(Q=0; Q<WLUT_WIDTH; Q++)
1280 resample_filter->filter_lut[Q] = (double)
1281 GetResizeFilterWeight(resize_filter,sqrt((double)Q)*r_scale);
1283 /* finished with the resize filter */
1284 resize_filter = DestroyResizeFilter(resize_filter);
1287 /* save the filter and the scaled ellipse bounds needed for filter */
1288 resample_filter->filter_def = resize_filter;
1289 resample_filter->F = resample_filter->support*resample_filter->support;
1293 Adjust the scaling of the default unit circle
1294 This assumes that any real scaling changes will always
1295 take place AFTER the filter method has been initialized.
1297 ScaleResampleFilter(resample_filter, 1.0, 0.0, 0.0, 1.0);
1300 /* This is old code kept as a reference only. It is very wrong,
1301 and I don't understand exactly what it was attempting to do.
1304 Create Normal Gaussian 2D Filter Weighted Lookup Table.
1305 A normal EWA guassual lookup would use exp(Q*ALPHA)
1306 where Q = distance squared from 0.0 (center) to 1.0 (edge)
1307 and ALPHA = -4.0*ln(2.0) ==> -2.77258872223978123767
1308 The table is of length 1024, and equates to support radius of 2.0
1309 thus needs to be scaled by ALPHA*4/1024 and any blur factor squared
1311 The above came from some reference code provided by Fred Weinhaus
1312 and seems to have been a guess that was appropriate for its use
1313 in a 3d perspective landscape mapping program.
1315 r_scale = -2.77258872223978123767/(WLUT_WIDTH*blur*blur);
1316 for(Q=0; Q<WLUT_WIDTH; Q++)
1317 resample_filter->filter_lut[Q] = exp((double)Q*r_scale);
1318 resample_filter->support = WLUT_WIDTH;
1323 #if defined(MAGICKCORE_OPENMP_SUPPORT)
1331 /* Scale radius so the filter LUT covers the full support range */
1332 r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
1333 if (IsMagickTrue(GetImageArtifact(resample_filter->image,"resample:verbose")) )
1335 /* Debug output of the filter weighting LUT
1336 Gnuplot the LUT with hoizontal adjusted to 'r' using...
1337 plot [0:2][-.2:1] "lut.dat" using (sqrt($0/1024)*2):1 with lines
1338 The filter values is normalized for comparision
1341 printf("# Resampling Filter LUT (%d values)\n", WLUT_WIDTH);
1343 printf("# Note: values in table are using a squared radius lookup.\n");
1344 printf("# And the whole table represents the filters support.\n");
1345 printf("\n"); /* generates a 'break' in gnuplot if multiple outputs */
1346 for(Q=0; Q<WLUT_WIDTH; Q++)
1347 printf("%8.*g %.*g\n",
1348 GetMagickPrecision(),sqrt((double)Q)*r_scale,
1349 GetMagickPrecision(),resample_filter->filter_lut[Q] );
1351 /* output the above once only for each image, and each setting */
1352 (void) DeleteImageArtifact(resample_filter->image,"resample:verbose");
1354 #endif /* FILTER_LUT */
1359 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1363 % S e t R e s a m p l e F i l t e r I n t e r p o l a t e M e t h o d %
1367 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1369 % SetResampleFilterInterpolateMethod() sets the resample filter interpolation
1372 % The format of the SetResampleFilterInterpolateMethod method is:
1374 % MagickBooleanType SetResampleFilterInterpolateMethod(
1375 % ResampleFilter *resample_filter,const InterpolateMethod method)
1377 % A description of each parameter follows:
1379 % o resample_filter: the resample filter.
1381 % o method: the interpolation method.
1384 MagickExport MagickBooleanType SetResampleFilterInterpolateMethod(
1385 ResampleFilter *resample_filter,const PixelInterpolateMethod method)
1387 assert(resample_filter != (ResampleFilter *) NULL);
1388 assert(resample_filter->signature == MagickSignature);
1389 assert(resample_filter->image != (Image *) NULL);
1390 if (resample_filter->debug != MagickFalse)
1391 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
1392 resample_filter->image->filename);
1393 resample_filter->interpolate=method;
1398 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1402 % S e t R e s a m p l e F i l t e r V i r t u a l P i x e l M e t h o d %
1406 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1408 % SetResampleFilterVirtualPixelMethod() changes the virtual pixel method
1409 % associated with the specified resample filter.
1411 % The format of the SetResampleFilterVirtualPixelMethod method is:
1413 % MagickBooleanType SetResampleFilterVirtualPixelMethod(
1414 % ResampleFilter *resample_filter,const VirtualPixelMethod method)
1416 % A description of each parameter follows:
1418 % o resample_filter: the resample filter.
1420 % o method: the virtual pixel method.
1423 MagickExport MagickBooleanType SetResampleFilterVirtualPixelMethod(
1424 ResampleFilter *resample_filter,const VirtualPixelMethod method)
1426 assert(resample_filter != (ResampleFilter *) NULL);
1427 assert(resample_filter->signature == MagickSignature);
1428 assert(resample_filter->image != (Image *) NULL);
1429 if (resample_filter->debug != MagickFalse)
1430 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
1431 resample_filter->image->filename);
1432 resample_filter->virtual_pixel=method;
1433 if (method != UndefinedVirtualPixelMethod)
1434 (void) SetCacheViewVirtualPixelMethod(resample_filter->view,method);