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 1999-2012 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/token.h"
63 #include "MagickCore/transform.h"
64 #include "MagickCore/signature-private.h"
65 #include "MagickCore/utility.h"
66 #include "MagickCore/utility-private.h"
68 EWA Resampling Options
71 /* select ONE resampling method */
72 #define EWA 1 /* Normal EWA handling - raw or clamped */
73 /* if 0 then use "High Quality EWA" */
74 #define EWA_CLAMP 1 /* EWA Clamping from Nicolas Robidoux */
76 #define FILTER_LUT 1 /* Use a LUT rather then direct filter calls */
78 /* output debugging information */
79 #define DEBUG_ELLIPSE 0 /* output ellipse info for debug */
80 #define DEBUG_HIT_MISS 0 /* output hit/miss pixels (as gnuplot commands) */
81 #define DEBUG_NO_PIXEL_HIT 0 /* Make pixels that fail to hit anything - RED */
84 #define WLUT_WIDTH 1024 /* size of the filter cache */
90 struct _ResampleFilter
104 /* Information about image being resampled */
108 PixelInterpolateMethod
117 /* processing settings needed */
126 /* current ellipitical area being resampled around center point */
129 Vlimit, Ulimit, Uwidth, slope;
132 /* LUT of weights for filtered average in elliptical area */
134 filter_lut[WLUT_WIDTH];
136 /* Use a Direct call to the filter functions */
144 /* the practical working support of the filter */
153 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
157 % A c q u i r e R e s a m p l e I n f o %
161 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
163 % AcquireResampleFilter() initializes the information resample needs do to a
164 % scaled lookup of a color from an image, using area sampling.
166 % The algorithm is based on a Elliptical Weighted Average, where the pixels
167 % found in a large elliptical area is averaged together according to a
168 % weighting (filter) function. For more details see "Fundamentals of Texture
169 % Mapping and Image Warping" a master's thesis by Paul.S.Heckbert, June 17,
170 % 1989. Available for free from, http://www.cs.cmu.edu/~ph/
172 % As EWA resampling (or any sort of resampling) can require a lot of
173 % calculations to produce a distorted scaling of the source image for each
174 % output pixel, the ResampleFilter structure generated holds that information
175 % between individual image resampling.
177 % This function will make the appropriate AcquireCacheView() calls
178 % to view the image, calling functions do not need to open a cache view.
181 % resample_filter=AcquireResampleFilter(image,exception);
182 % SetResampleFilter(resample_filter, GaussianFilter, 1.0);
183 % for (y=0; y < (ssize_t) image->rows; y++) {
184 % for (x=0; x < (ssize_t) image->columns; x++) {
186 % ScaleResampleFilter(resample_filter, ... scaling vectors ...);
187 % (void) ResamplePixelColor(resample_filter,u,v,&pixel);
188 % ... assign resampled pixel value ...
191 % DestroyResampleFilter(resample_filter);
193 % The format of the AcquireResampleFilter method is:
195 % ResampleFilter *AcquireResampleFilter(const Image *image,
196 % ExceptionInfo *exception)
198 % A description of each parameter follows:
200 % o image: the image.
202 % o exception: return any errors or warnings in this structure.
205 MagickExport ResampleFilter *AcquireResampleFilter(const Image *image,
206 ExceptionInfo *exception)
208 register ResampleFilter
211 assert(image != (Image *) NULL);
212 assert(image->signature == MagickSignature);
213 if (image->debug != MagickFalse)
214 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",image->filename);
215 assert(exception != (ExceptionInfo *) NULL);
216 assert(exception->signature == MagickSignature);
218 resample_filter=(ResampleFilter *) AcquireMagickMemory(
219 sizeof(*resample_filter));
220 if (resample_filter == (ResampleFilter *) NULL)
221 ThrowFatalException(ResourceLimitFatalError,"MemoryAllocationFailed");
222 (void) ResetMagickMemory(resample_filter,0,sizeof(*resample_filter));
224 resample_filter->exception=exception;
225 resample_filter->image=ReferenceImage((Image *) image);
226 resample_filter->view=AcquireCacheView(resample_filter->image);
228 resample_filter->debug=IsEventLogging();
229 resample_filter->signature=MagickSignature;
231 resample_filter->image_area=(ssize_t) (image->columns*image->rows);
232 resample_filter->average_defined = MagickFalse;
234 /* initialise the resampling filter settings */
235 SetResampleFilter(resample_filter, image->filter);
236 (void) SetResampleFilterInterpolateMethod(resample_filter,image->interpolate);
237 (void) SetResampleFilterVirtualPixelMethod(resample_filter,
238 GetImageVirtualPixelMethod(image));
239 return(resample_filter);
243 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
247 % D e s t r o y R e s a m p l e I n f o %
251 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
253 % DestroyResampleFilter() finalizes and cleans up the resampling
254 % resample_filter as returned by AcquireResampleFilter(), freeing any memory
255 % or other information as needed.
257 % The format of the DestroyResampleFilter method is:
259 % ResampleFilter *DestroyResampleFilter(ResampleFilter *resample_filter)
261 % A description of each parameter follows:
263 % o resample_filter: resampling information structure
266 MagickExport ResampleFilter *DestroyResampleFilter(
267 ResampleFilter *resample_filter)
269 assert(resample_filter != (ResampleFilter *) NULL);
270 assert(resample_filter->signature == MagickSignature);
271 assert(resample_filter->image != (Image *) NULL);
272 if (resample_filter->debug != MagickFalse)
273 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
274 resample_filter->image->filename);
275 resample_filter->view=DestroyCacheView(resample_filter->view);
276 resample_filter->image=DestroyImage(resample_filter->image);
278 resample_filter->filter_def=DestroyResizeFilter(resample_filter->filter_def);
280 resample_filter->signature=(~MagickSignature);
281 resample_filter=(ResampleFilter *) RelinquishMagickMemory(resample_filter);
282 return(resample_filter);
286 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
290 % R e s a m p l e P i x e l C o l o r %
294 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
296 % ResamplePixelColor() samples the pixel values surrounding the location
297 % given using an elliptical weighted average, at the scale previously
298 % calculated, and in the most efficent manner possible for the
299 % VirtualPixelMethod setting.
301 % The format of the ResamplePixelColor method is:
303 % MagickBooleanType ResamplePixelColor(ResampleFilter *resample_filter,
304 % const double u0,const double v0,PixelInfo *pixel)
306 % A description of each parameter follows:
308 % o resample_filter: the resample filter.
310 % o u0,v0: A double representing the center of the area to resample,
311 % The distortion transformed transformed x,y coordinate.
313 % o pixel: the resampled pixel is returned here.
316 MagickExport MagickBooleanType ResamplePixelColor(
317 ResampleFilter *resample_filter,const double u0,const double v0,
323 ssize_t u,v, v1, v2, uw, hit;
326 double divisor_c,divisor_m;
327 register double weight;
328 register const Quantum *pixels;
329 assert(resample_filter != (ResampleFilter *) NULL);
330 assert(resample_filter->signature == MagickSignature);
333 /* GetPixelInfo(resample_filter->image,pixel); */
334 if ( resample_filter->do_interpolate ) {
335 status=InterpolatePixelInfo(resample_filter->image,resample_filter->view,
336 resample_filter->interpolate,u0,v0,pixel,resample_filter->exception);
341 (void) FormatLocaleFile(stderr, "u0=%lf; v0=%lf;\n", u0, v0);
345 Does resample area Miss the image?
346 And is that area a simple solid color - then return that color
349 switch ( resample_filter->virtual_pixel ) {
350 case BackgroundVirtualPixelMethod:
351 case TransparentVirtualPixelMethod:
352 case BlackVirtualPixelMethod:
353 case GrayVirtualPixelMethod:
354 case WhiteVirtualPixelMethod:
355 case MaskVirtualPixelMethod:
356 if ( resample_filter->limit_reached
357 || u0 + resample_filter->Ulimit < 0.0
358 || u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
359 || v0 + resample_filter->Vlimit < 0.0
360 || v0 - resample_filter->Vlimit > (double) resample_filter->image->rows
365 case UndefinedVirtualPixelMethod:
366 case EdgeVirtualPixelMethod:
367 if ( ( u0 + resample_filter->Ulimit < 0.0 && v0 + resample_filter->Vlimit < 0.0 )
368 || ( u0 + resample_filter->Ulimit < 0.0
369 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows )
370 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
371 && v0 + resample_filter->Vlimit < 0.0 )
372 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
373 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows )
377 case HorizontalTileVirtualPixelMethod:
378 if ( v0 + resample_filter->Vlimit < 0.0
379 || v0 - resample_filter->Vlimit > (double) resample_filter->image->rows
381 hit++; /* outside the horizontally tiled images. */
383 case VerticalTileVirtualPixelMethod:
384 if ( u0 + resample_filter->Ulimit < 0.0
385 || u0 - resample_filter->Ulimit > (double) resample_filter->image->columns
387 hit++; /* outside the vertically tiled images. */
389 case DitherVirtualPixelMethod:
390 if ( ( u0 + resample_filter->Ulimit < -32.0 && v0 + resample_filter->Vlimit < -32.0 )
391 || ( u0 + resample_filter->Ulimit < -32.0
392 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+32.0 )
393 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+32.0
394 && v0 + resample_filter->Vlimit < -32.0 )
395 || ( u0 - resample_filter->Ulimit > (double) resample_filter->image->columns+32.0
396 && v0 - resample_filter->Vlimit > (double) resample_filter->image->rows+32.0 )
400 case TileVirtualPixelMethod:
401 case MirrorVirtualPixelMethod:
402 case RandomVirtualPixelMethod:
403 case HorizontalTileEdgeVirtualPixelMethod:
404 case VerticalTileEdgeVirtualPixelMethod:
405 case CheckerTileVirtualPixelMethod:
406 /* resampling of area is always needed - no VP limits */
410 /* whole area is a solid color -- just return that color */
411 status=InterpolatePixelInfo(resample_filter->image,
412 resample_filter->view,IntegerInterpolatePixel,u0,v0,pixel,
413 resample_filter->exception);
418 Scaling limits reached, return an 'averaged' result.
420 if ( resample_filter->limit_reached ) {
421 switch ( resample_filter->virtual_pixel ) {
422 /* This is always handled by the above, so no need.
423 case BackgroundVirtualPixelMethod:
424 case ConstantVirtualPixelMethod:
425 case TransparentVirtualPixelMethod:
426 case GrayVirtualPixelMethod,
427 case WhiteVirtualPixelMethod
428 case MaskVirtualPixelMethod:
430 case UndefinedVirtualPixelMethod:
431 case EdgeVirtualPixelMethod:
432 case DitherVirtualPixelMethod:
433 case HorizontalTileEdgeVirtualPixelMethod:
434 case VerticalTileEdgeVirtualPixelMethod:
435 /* We need an average edge pixel, from the correct edge!
436 How should I calculate an average edge color?
437 Just returning an averaged neighbourhood,
438 works well in general, but falls down for TileEdge methods.
439 This needs to be done properly!!!!!!
441 status=InterpolatePixelInfo(resample_filter->image,
442 resample_filter->view,AverageInterpolatePixel,u0,v0,pixel,
443 resample_filter->exception);
445 case HorizontalTileVirtualPixelMethod:
446 case VerticalTileVirtualPixelMethod:
447 /* just return the background pixel - Is there more direct way? */
448 status=InterpolatePixelInfo(resample_filter->image,
449 resample_filter->view,IntegerInterpolatePixel,-1.0,-1.0,pixel,
450 resample_filter->exception);
452 case TileVirtualPixelMethod:
453 case MirrorVirtualPixelMethod:
454 case RandomVirtualPixelMethod:
455 case CheckerTileVirtualPixelMethod:
457 /* generate a average color of the WHOLE image */
458 if ( resample_filter->average_defined == MagickFalse ) {
465 GetPixelInfo(resample_filter->image,(PixelInfo *)
466 &resample_filter->average_pixel);
467 resample_filter->average_defined=MagickTrue;
469 /* Try to get an averaged pixel color of whole image */
470 average_image=ResizeImage(resample_filter->image,1,1,BoxFilter,
471 resample_filter->exception);
472 if (average_image == (Image *) NULL)
474 *pixel=resample_filter->average_pixel; /* FAILED */
477 average_view=AcquireCacheView(average_image);
478 pixels=GetCacheViewVirtualPixels(average_view,0,0,1,1,
479 resample_filter->exception);
480 if (pixels == (const Quantum *) NULL) {
481 average_view=DestroyCacheView(average_view);
482 average_image=DestroyImage(average_image);
483 *pixel=resample_filter->average_pixel; /* FAILED */
486 GetPixelInfoPixel(resample_filter->image,pixels,
487 &(resample_filter->average_pixel));
488 average_view=DestroyCacheView(average_view);
489 average_image=DestroyImage(average_image);
491 if ( resample_filter->virtual_pixel == CheckerTileVirtualPixelMethod )
493 /* CheckerTile is avergae of image average half background */
494 /* FUTURE: replace with a 50% blend of both pixels */
496 weight = QuantumScale*((MagickRealType)
497 resample_filter->average_pixel.alpha);
498 resample_filter->average_pixel.red *= weight;
499 resample_filter->average_pixel.green *= weight;
500 resample_filter->average_pixel.blue *= weight;
503 weight = QuantumScale*((MagickRealType)
504 resample_filter->image->background_color.alpha);
505 resample_filter->average_pixel.red +=
506 weight*resample_filter->image->background_color.red;
507 resample_filter->average_pixel.green +=
508 weight*resample_filter->image->background_color.green;
509 resample_filter->average_pixel.blue +=
510 weight*resample_filter->image->background_color.blue;
511 resample_filter->average_pixel.alpha +=
512 resample_filter->image->background_color.alpha;
515 resample_filter->average_pixel.red /= divisor_c;
516 resample_filter->average_pixel.green /= divisor_c;
517 resample_filter->average_pixel.blue /= divisor_c;
518 resample_filter->average_pixel.alpha /= 2;
522 *pixel=resample_filter->average_pixel;
529 Initialize weighted average data collection
534 pixel->red = pixel->green = pixel->blue = 0.0;
535 if (pixel->colorspace == CMYKColorspace)
537 if (pixel->matte != MagickFalse)
541 Determine the parellelogram bounding box fitted to the ellipse
542 centered at u0,v0. This area is bounding by the lines...
544 v1 = (ssize_t)ceil(v0 - resample_filter->Vlimit); /* range of scan lines */
545 v2 = (ssize_t)floor(v0 + resample_filter->Vlimit);
547 /* scan line start and width accross the parallelogram */
548 u1 = u0 + (v1-v0)*resample_filter->slope - resample_filter->Uwidth;
549 uw = (ssize_t)(2.0*resample_filter->Uwidth)+1;
552 (void) FormatLocaleFile(stderr, "v1=%ld; v2=%ld\n", (long)v1, (long)v2);
553 (void) FormatLocaleFile(stderr, "u1=%ld; uw=%ld\n", (long)u1, (long)uw);
555 # define DEBUG_HIT_MISS 0 /* only valid if DEBUG_ELLIPSE is enabled */
559 Do weighted resampling of all pixels, within the scaled ellipse,
560 bound by a Parellelogram fitted to the ellipse.
562 DDQ = 2*resample_filter->A;
563 for( v=v1; v<=v2; v++ ) {
565 long uu = ceil(u1); /* actual pixel location (for debug only) */
566 (void) FormatLocaleFile(stderr, "# scan line from pixel %ld, %ld\n", (long)uu, (long)v);
568 u = (ssize_t)ceil(u1); /* first pixel in scanline */
569 u1 += resample_filter->slope; /* start of next scan line */
572 /* location of this first pixel, relative to u0,v0 */
576 /* Q = ellipse quotent ( if Q<F then pixel is inside ellipse) */
577 Q = (resample_filter->A*U + resample_filter->B*V)*U + resample_filter->C*V*V;
578 DQ = resample_filter->A*(2.0*U+1) + resample_filter->B*V;
580 /* get the scanline of pixels for this v */
581 pixels=GetCacheViewVirtualPixels(resample_filter->view,u,v,(size_t) uw,
582 1,resample_filter->exception);
583 if (pixels == (const Quantum *) NULL)
586 /* count up the weighted pixel colors */
587 for( u=0; u<uw; u++ ) {
589 /* Note that the ellipse has been pre-scaled so F = WLUT_WIDTH */
590 if ( Q < (double)WLUT_WIDTH ) {
591 weight = resample_filter->filter_lut[(int)Q];
593 /* Note that the ellipse has been pre-scaled so F = support^2 */
594 if ( Q < (double)resample_filter->F ) {
595 weight = GetResizeFilterWeight(resample_filter->filter_def,
596 sqrt(Q)); /* a SquareRoot! Arrggghhhhh... */
599 pixel->alpha += weight*GetPixelAlpha(resample_filter->image,pixels);
602 if (pixel->matte != MagickFalse)
603 weight *= QuantumScale*((MagickRealType) GetPixelAlpha(resample_filter->image,pixels));
604 pixel->red += weight*GetPixelRed(resample_filter->image,pixels);
605 pixel->green += weight*GetPixelGreen(resample_filter->image,pixels);
606 pixel->blue += weight*GetPixelBlue(resample_filter->image,pixels);
607 if (pixel->colorspace == CMYKColorspace)
608 pixel->black += weight*GetPixelBlack(resample_filter->image,pixels);
613 /* mark the pixel according to hit/miss of the ellipse */
614 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 3\n",
615 (long)uu-.1,(double)v-.1,(long)uu+.1,(long)v+.1);
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);
619 (void) FormatLocaleFile(stderr, "set arrow from %lf,%lf to %lf,%lf nohead ls 1\n",
620 (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);
628 pixels+=GetPixelChannels(resample_filter->image);
634 (void) FormatLocaleFile(stderr, "Hit=%ld; Total=%ld;\n", (long)hit, (long)uw*(v2-v1) );
638 Result sanity check -- this should NOT happen
641 /* not enough pixels in resampling, resort to direct interpolation */
642 #if DEBUG_NO_PIXEL_HIT
643 pixel->alpha = pixel->red = pixel->green = pixel->blue = 0;
644 pixel->red = QuantumRange; /* show pixels for which EWA fails */
646 status=InterpolatePixelInfo(resample_filter->image,
647 resample_filter->view,resample_filter->interpolate,u0,v0,pixel,
648 resample_filter->exception);
654 Finialize results of resampling
656 divisor_m = 1.0/divisor_m;
657 pixel->alpha = (MagickRealType) ClampToQuantum(divisor_m*pixel->alpha);
658 divisor_c = 1.0/divisor_c;
659 pixel->red = (MagickRealType) ClampToQuantum(divisor_c*pixel->red);
660 pixel->green = (MagickRealType) ClampToQuantum(divisor_c*pixel->green);
661 pixel->blue = (MagickRealType) ClampToQuantum(divisor_c*pixel->blue);
662 if (pixel->colorspace == CMYKColorspace)
663 pixel->black = (MagickRealType) ClampToQuantum(divisor_c*pixel->black);
669 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
673 - C l a m p U p A x e s %
677 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
679 % ClampUpAxes() function converts the input vectors into a major and
680 % minor axis unit vectors, and their magnitude. This allows us to
681 % ensure that the ellipse generated is never smaller than the unit
682 % circle and thus never too small for use in EWA resampling.
684 % This purely mathematical 'magic' was provided by Professor Nicolas
685 % Robidoux and his Masters student Chantal Racette.
687 % Reference: "We Recommend Singular Value Decomposition", David Austin
688 % http://www.ams.org/samplings/feature-column/fcarc-svd
690 % By generating major and minor axis vectors, we can actually use the
691 % ellipse in its "canonical form", by remapping the dx,dy of the
692 % sampled point into distances along the major and minor axis unit
695 % Reference: http://en.wikipedia.org/wiki/Ellipse#Canonical_form
697 static inline void ClampUpAxes(const double dux,
703 double *major_unit_x,
704 double *major_unit_y,
705 double *minor_unit_x,
706 double *minor_unit_y)
709 * ClampUpAxes takes an input 2x2 matrix
711 * [ a b ] = [ dux duy ]
712 * [ c d ] = [ dvx dvy ]
714 * and computes from it the major and minor axis vectors [major_x,
715 * major_y] and [minor_x,minor_y] of the smallest ellipse containing
716 * both the unit disk and the ellipse which is the image of the unit
717 * disk by the linear transformation
719 * [ dux duy ] [S] = [s]
720 * [ dvx dvy ] [T] = [t]
722 * (The vector [S,T] is the difference between a position in output
723 * space and [X,Y]; the vector [s,t] is the difference between a
724 * position in input space and [x,y].)
729 * major_mag is the half-length of the major axis of the "new"
732 * minor_mag is the half-length of the minor axis of the "new"
735 * major_unit_x is the x-coordinate of the major axis direction vector
736 * of both the "old" and "new" ellipses.
738 * major_unit_y is the y-coordinate of the major axis direction vector.
740 * minor_unit_x is the x-coordinate of the minor axis direction vector.
742 * minor_unit_y is the y-coordinate of the minor axis direction vector.
744 * Unit vectors are useful for computing projections, in particular,
745 * to compute the distance between a point in output space and the
746 * center of a unit disk in output space, using the position of the
747 * corresponding point [s,t] in input space. Following the clamping,
748 * the square of this distance is
750 * ( ( s * major_unit_x + t * major_unit_y ) / major_mag )^2
752 * ( ( s * minor_unit_x + t * minor_unit_y ) / minor_mag )^2
754 * If such distances will be computed for many [s,t]'s, it makes
755 * sense to actually compute the reciprocal of major_mag and
756 * minor_mag and multiply them by the above unit lengths.
758 * Now, if you want to modify the input pair of tangent vectors so
759 * that it defines the modified ellipse, all you have to do is set
761 * newdux = major_mag * major_unit_x
762 * newdvx = major_mag * major_unit_y
763 * newduy = minor_mag * minor_unit_x = minor_mag * -major_unit_y
764 * newdvy = minor_mag * minor_unit_y = minor_mag * major_unit_x
766 * and use these tangent vectors as if they were the original ones.
767 * Usually, this is a drastic change in the tangent vectors even if
768 * the singular values are not clamped; for example, the minor axis
769 * vector always points in a direction which is 90 degrees
770 * counterclockwise from the direction of the major axis vector.
775 * GOAL: Fix things so that the pullback, in input space, of a disk
776 * of radius r in output space is an ellipse which contains, at
777 * least, a disc of radius r. (Make this hold for any r>0.)
779 * ESSENCE OF THE METHOD: Compute the product of the first two
780 * factors of an SVD of the linear transformation defining the
781 * ellipse and make sure that both its columns have norm at least 1.
782 * Because rotations and reflexions map disks to themselves, it is
783 * not necessary to compute the third (rightmost) factor of the SVD.
785 * DETAILS: Find the singular values and (unit) left singular
786 * vectors of Jinv, clampling up the singular values to 1, and
787 * multiply the unit left singular vectors by the new singular
788 * values in order to get the minor and major ellipse axis vectors.
790 * Image resampling context:
792 * The Jacobian matrix of the transformation at the output point
793 * under consideration is defined as follows:
795 * Consider the transformation (x,y) -> (X,Y) from input locations
796 * to output locations. (Anthony Thyssen, elsewhere in resample.c,
797 * uses the notation (u,v) -> (x,y).)
799 * The Jacobian matrix of the transformation at (x,y) is equal to
801 * J = [ A, B ] = [ dX/dx, dX/dy ]
802 * [ C, D ] [ dY/dx, dY/dy ]
804 * that is, the vector [A,C] is the tangent vector corresponding to
805 * input changes in the horizontal direction, and the vector [B,D]
806 * is the tangent vector corresponding to input changes in the
807 * vertical direction.
809 * In the context of resampling, it is natural to use the inverse
810 * Jacobian matrix Jinv because resampling is generally performed by
811 * pulling pixel locations in the output image back to locations in
812 * the input image. Jinv is
814 * Jinv = [ a, b ] = [ dx/dX, dx/dY ]
815 * [ c, d ] [ dy/dX, dy/dY ]
817 * Note: Jinv can be computed from J with the following matrix
820 * Jinv = 1/(A*D-B*C) [ D, -B ]
823 * What we do is modify Jinv so that it generates an ellipse which
824 * is as close as possible to the original but which contains the
825 * unit disk. This can be accomplished as follows:
831 * be an SVD decomposition of Jinv. (The SVD is not unique, but the
832 * final ellipse does not depend on the particular SVD.)
834 * We could clamp up the entries of the diagonal matrix Sigma so
835 * that they are at least 1, and then set
837 * Jinv = U newSigma V^T.
839 * However, we do not need to compute V for the following reason:
840 * V^T is an orthogonal matrix (that is, it represents a combination
841 * of rotations and reflexions) so that it maps the unit circle to
842 * itself. For this reason, the exact value of V does not affect the
843 * final ellipse, and we can choose V to be the identity
848 * In the end, we return the two diagonal entries of newSigma
849 * together with the two columns of U.
852 * ClampUpAxes was written by Nicolas Robidoux and Chantal Racette
853 * of Laurentian University with insightful suggestions from Anthony
854 * Thyssen and funding from the National Science and Engineering
855 * Research Council of Canada. It is distinguished from its
856 * predecessors by its efficient handling of degenerate cases.
858 * The idea of clamping up the EWA ellipse's major and minor axes so
859 * that the result contains the reconstruction kernel filter support
860 * is taken from Andreas Gustaffson's Masters thesis "Interactive
861 * Image Warping", Helsinki University of Technology, Faculty of
862 * Information Technology, 59 pages, 1993 (see Section 3.6).
864 * The use of the SVD to clamp up the singular values of the
865 * Jacobian matrix of the pullback transformation for EWA resampling
866 * is taken from the astrophysicist Craig DeForest. It is
867 * implemented in his PDL::Transform code (PDL = Perl Data
870 const double a = dux;
871 const double b = duy;
872 const double c = dvx;
873 const double d = dvy;
875 * n is the matrix Jinv * transpose(Jinv). Eigenvalues of n are the
876 * squares of the singular values of Jinv.
878 const double aa = a*a;
879 const double bb = b*b;
880 const double cc = c*c;
881 const double dd = d*d;
883 * Eigenvectors of n are left singular vectors of Jinv.
885 const double n11 = aa+bb;
886 const double n12 = a*c+b*d;
887 const double n21 = n12;
888 const double n22 = cc+dd;
889 const double det = a*d-b*c;
890 const double twice_det = det+det;
891 const double frobenius_squared = n11+n22;
892 const double discriminant =
893 (frobenius_squared+twice_det)*(frobenius_squared-twice_det);
894 const double sqrt_discriminant = sqrt(discriminant);
896 * s1 is the largest singular value of the inverse Jacobian
897 * matrix. In other words, its reciprocal is the smallest singular
898 * value of the Jacobian matrix itself.
899 * If s1 = 0, both singular values are 0, and any orthogonal pair of
900 * left and right factors produces a singular decomposition of Jinv.
903 * Initially, we only compute the squares of the singular values.
905 const double s1s1 = 0.5*(frobenius_squared+sqrt_discriminant);
907 * s2 the smallest singular value of the inverse Jacobian
908 * matrix. Its reciprocal is the largest singular value of the
909 * Jacobian matrix itself.
911 const double s2s2 = 0.5*(frobenius_squared-sqrt_discriminant);
912 const double s1s1minusn11 = s1s1-n11;
913 const double s1s1minusn22 = s1s1-n22;
915 * u1, the first column of the U factor of a singular decomposition
916 * of Jinv, is a (non-normalized) left singular vector corresponding
917 * to s1. It has entries u11 and u21. We compute u1 from the fact
918 * that it is an eigenvector of n corresponding to the eigenvalue
921 const double s1s1minusn11_squared = s1s1minusn11*s1s1minusn11;
922 const double s1s1minusn22_squared = s1s1minusn22*s1s1minusn22;
924 * The following selects the largest row of n-s1^2 I as the one
925 * which is used to find the eigenvector. If both s1^2-n11 and
926 * s1^2-n22 are zero, n-s1^2 I is the zero matrix. In that case,
927 * any vector is an eigenvector; in addition, norm below is equal to
928 * zero, and, in exact arithmetic, this is the only case in which
929 * norm = 0. So, setting u1 to the simple but arbitrary vector [1,0]
930 * if norm = 0 safely takes care of all cases.
932 const double temp_u11 =
933 ( (s1s1minusn11_squared>=s1s1minusn22_squared) ? n12 : s1s1minusn22 );
934 const double temp_u21 =
935 ( (s1s1minusn11_squared>=s1s1minusn22_squared) ? s1s1minusn11 : n21 );
936 const double norm = sqrt(temp_u11*temp_u11+temp_u21*temp_u21);
938 * Finalize the entries of first left singular vector (associated
939 * with the largest singular value).
941 const double u11 = ( (norm>0.0) ? temp_u11/norm : 1.0 );
942 const double u21 = ( (norm>0.0) ? temp_u21/norm : 0.0 );
944 * Clamp the singular values up to 1.
946 *major_mag = ( (s1s1<=1.0) ? 1.0 : sqrt(s1s1) );
947 *minor_mag = ( (s2s2<=1.0) ? 1.0 : sqrt(s2s2) );
949 * Return the unit major and minor axis direction vectors.
953 *minor_unit_x = -u21;
959 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
963 % S c a l e R e s a m p l e F i l t e r %
967 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
969 % ScaleResampleFilter() does all the calculations needed to resample an image
970 % at a specific scale, defined by two scaling vectors. This not using
971 % a orthogonal scaling, but two distorted scaling vectors, to allow the
972 % generation of a angled ellipse.
974 % As only two deritive scaling vectors are used the center of the ellipse
975 % must be the center of the lookup. That is any curvature that the
976 % distortion may produce is discounted.
978 % The input vectors are produced by either finding the derivitives of the
979 % distortion function, or the partial derivitives from a distortion mapping.
980 % They do not need to be the orthogonal dx,dy scaling vectors, but can be
981 % calculated from other derivatives. For example you could use dr,da/r
982 % polar coordinate vector scaling vectors
984 % If u,v = DistortEquation(x,y) OR u = Fu(x,y); v = Fv(x,y)
985 % Then the scaling vectors are determined from the deritives...
986 % du/dx, dv/dx and du/dy, dv/dy
987 % If the resulting scaling vectors is othogonally aligned then...
988 % dv/dx = 0 and du/dy = 0
989 % Producing an othogonally alligned ellipse in source space for the area to
992 % Note that scaling vectors are different to argument order. Argument order
993 % is the general order the deritives are extracted from the distortion
994 % equations, and not the scaling vectors. As such the middle two vaules
995 % may be swapped from what you expect. Caution is advised.
997 % WARNING: It is assumed that any SetResampleFilter() method call will
998 % always be performed before the ScaleResampleFilter() method, so that the
999 % size of the ellipse will match the support for the resampling filter being
1002 % The format of the ScaleResampleFilter method is:
1004 % void ScaleResampleFilter(const ResampleFilter *resample_filter,
1005 % const double dux,const double duy,const double dvx,const double dvy)
1007 % A description of each parameter follows:
1009 % o resample_filter: the resampling resample_filterrmation defining the
1010 % image being resampled
1012 % o dux,duy,dvx,dvy:
1013 % The deritives or scaling vectors defining the EWA ellipse.
1014 % NOTE: watch the order, which is based on the order deritives
1015 % are usally determined from distortion equations (see above).
1016 % The middle two values may need to be swapped if you are thinking
1017 % in terms of scaling vectors.
1020 MagickExport void ScaleResampleFilter(ResampleFilter *resample_filter,
1021 const double dux,const double duy,const double dvx,const double dvy)
1025 assert(resample_filter != (ResampleFilter *) NULL);
1026 assert(resample_filter->signature == MagickSignature);
1028 resample_filter->limit_reached = MagickFalse;
1030 /* A 'point' filter forces use of interpolation instead of area sampling */
1031 if ( resample_filter->filter == PointFilter )
1032 return; /* EWA turned off - nothing to do */
1035 (void) FormatLocaleFile(stderr, "# -----\n" );
1036 (void) FormatLocaleFile(stderr, "dux=%lf; dvx=%lf; duy=%lf; dvy=%lf;\n",
1037 dux, dvx, duy, dvy);
1040 /* Find Ellipse Coefficents such that
1041 A*u^2 + B*u*v + C*v^2 = F
1042 With u,v relative to point around which we are resampling.
1043 And the given scaling dx,dy vectors in u,v space
1044 du/dx,dv/dx and du/dy,dv/dy
1047 /* Direct conversion of derivatives into elliptical coefficients
1048 However when magnifying images, the scaling vectors will be small
1049 resulting in a ellipse that is too small to sample properly.
1050 As such we need to clamp the major/minor axis to a minumum of 1.0
1051 to prevent it getting too small.
1061 ClampUpAxes(dux,dvx,duy,dvy, &major_mag, &minor_mag,
1062 &major_x, &major_y, &minor_x, &minor_y);
1063 major_x *= major_mag; major_y *= major_mag;
1064 minor_x *= minor_mag; minor_y *= minor_mag;
1066 (void) FormatLocaleFile(stderr, "major_x=%lf; major_y=%lf; minor_x=%lf; minor_y=%lf;\n",
1067 major_x, major_y, minor_x, minor_y);
1069 A = major_y*major_y+minor_y*minor_y;
1070 B = -2.0*(major_x*major_y+minor_x*minor_y);
1071 C = major_x*major_x+minor_x*minor_x;
1072 F = major_mag*minor_mag;
1073 F *= F; /* square it */
1075 #else /* raw unclamped EWA */
1076 A = dvx*dvx+dvy*dvy;
1077 B = -2.0*(dux*dvx+duy*dvy);
1078 C = dux*dux+duy*duy;
1079 F = dux*dvy-duy*dvx;
1080 F *= F; /* square it */
1081 #endif /* EWA_CLAMP */
1085 This Paul Heckbert's "Higher Quality EWA" formula, from page 60 in his
1086 thesis, which adds a unit circle to the elliptical area so as to do both
1087 Reconstruction and Prefiltering of the pixels in the resampling. It also
1088 means it is always likely to have at least 4 pixels within the area of the
1089 ellipse, for weighted averaging. No scaling will result with F == 4.0 and
1090 a circle of radius 2.0, and F smaller than this means magnification is
1093 NOTE: This method produces a very blury result at near unity scale while
1094 producing perfect results for strong minitification and magnifications.
1096 However filter support is fixed to 2.0 (no good for Windowed Sinc filters)
1098 A = dvx*dvx+dvy*dvy+1;
1099 B = -2.0*(dux*dvx+duy*dvy);
1100 C = dux*dux+duy*duy+1;
1105 (void) FormatLocaleFile(stderr, "A=%lf; B=%lf; C=%lf; F=%lf\n", A,B,C,F);
1107 /* Figure out the various information directly about the ellipse.
1108 This information currently not needed at this time, but may be
1109 needed later for better limit determination.
1111 It is also good to have as a record for future debugging
1113 { double alpha, beta, gamma, Major, Minor;
1114 double Eccentricity, Ellipse_Area, Ellipse_Angle;
1118 gamma = sqrt(beta*beta + B*B );
1120 if ( alpha - gamma <= MagickEpsilon )
1123 Major = sqrt(2*F/(alpha - gamma));
1124 Minor = sqrt(2*F/(alpha + gamma));
1126 (void) FormatLocaleFile(stderr, "# Major=%lf; Minor=%lf\n", Major, Minor );
1128 /* other information about ellipse include... */
1129 Eccentricity = Major/Minor;
1130 Ellipse_Area = MagickPI*Major*Minor;
1131 Ellipse_Angle = atan2(B, A-C);
1133 (void) FormatLocaleFile(stderr, "# Angle=%lf Area=%lf\n",
1134 RadiansToDegrees(Ellipse_Angle), Ellipse_Area);
1138 /* If one or both of the scaling vectors is impossibly large
1139 (producing a very large raw F value), we may as well not bother
1140 doing any form of resampling since resampled area is very large.
1141 In this case some alternative means of pixel sampling, such as
1142 the average of the whole image is needed to get a reasonable
1143 result. Calculate only as needed.
1145 if ( (4*A*C - B*B) > MagickHuge ) {
1146 resample_filter->limit_reached = MagickTrue;
1150 /* Scale ellipse to match the filters support
1151 (that is, multiply F by the square of the support).
1153 F *= resample_filter->support;
1154 F *= resample_filter->support;
1156 /* Orthogonal bounds of the ellipse */
1157 resample_filter->Ulimit = sqrt(C*F/(A*C-0.25*B*B));
1158 resample_filter->Vlimit = sqrt(A*F/(A*C-0.25*B*B));
1160 /* Horizontally aligned parallelogram fitted to Ellipse */
1161 resample_filter->Uwidth = sqrt(F/A); /* Half of the parallelogram width */
1162 resample_filter->slope = -B/(2.0*A); /* Reciprocal slope of the parallelogram */
1165 (void) FormatLocaleFile(stderr, "Ulimit=%lf; Vlimit=%lf; UWidth=%lf; Slope=%lf;\n",
1166 resample_filter->Ulimit, resample_filter->Vlimit,
1167 resample_filter->Uwidth, resample_filter->slope );
1170 /* Check the absolute area of the parallelogram involved.
1171 * This limit needs more work, as it is too slow for larger images
1172 * with tiled views of the horizon.
1174 if ( (resample_filter->Uwidth * resample_filter->Vlimit)
1175 > (4.0*resample_filter->image_area)) {
1176 resample_filter->limit_reached = MagickTrue;
1180 /* Scale ellipse formula to directly index the Filter Lookup Table */
1181 { register double scale;
1183 /* scale so that F = WLUT_WIDTH; -- hardcoded */
1184 scale = (double)WLUT_WIDTH/F;
1186 /* scale so that F = resample_filter->F (support^2) */
1187 scale = resample_filter->F/F;
1189 resample_filter->A = A*scale;
1190 resample_filter->B = B*scale;
1191 resample_filter->C = C*scale;
1196 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1200 % S e t R e s a m p l e F i l t e r %
1204 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1206 % SetResampleFilter() set the resampling filter lookup table based on a
1207 % specific filter. Note that the filter is used as a radial filter not as a
1208 % two pass othogonally aligned resampling filter.
1210 % The default Filter, is Gaussian, which is the standard filter used by the
1211 % original paper on the Elliptical Weighted Everage Algorithm. However other
1212 % filters can also be used.
1214 % The format of the SetResampleFilter method is:
1216 % void SetResampleFilter(ResampleFilter *resample_filter,
1217 % const FilterTypes filter)
1219 % A description of each parameter follows:
1221 % o resample_filter: resampling resample_filterrmation structure
1223 % o filter: the resize filter for elliptical weighting LUT
1226 MagickExport void SetResampleFilter(ResampleFilter *resample_filter,
1227 const FilterTypes filter)
1232 assert(resample_filter != (ResampleFilter *) NULL);
1233 assert(resample_filter->signature == MagickSignature);
1235 resample_filter->do_interpolate = MagickFalse;
1236 resample_filter->filter = filter;
1238 if ( filter == PointFilter )
1240 resample_filter->do_interpolate = MagickTrue;
1241 return; /* EWA turned off - nothing more to do */
1244 /* Set a default cylindrical filter of a 'low blur' Jinc windowed Jinc */
1245 if ( filter == UndefinedFilter )
1246 resample_filter->filter = RobidouxFilter;
1248 resize_filter = AcquireResizeFilter(resample_filter->image,
1249 resample_filter->filter,MagickTrue,resample_filter->exception);
1250 if (resize_filter == (ResizeFilter *) NULL)
1252 (void) ThrowMagickException(resample_filter->exception,GetMagickModule(),
1253 ModuleError, "UnableToSetFilteringValue",
1254 "Fall back to default EWA gaussian filter");
1255 resample_filter->filter = PointFilter;
1258 /* Get the practical working support for the filter,
1259 * after any API call blur factors have been accoded for.
1262 resample_filter->support = GetResizeFilterSupport(resize_filter);
1264 resample_filter->support = 2.0; /* fixed support size for HQ-EWA */
1268 /* Fill the LUT with the weights from the selected filter function */
1273 /* Scale radius so the filter LUT covers the full support range */
1274 r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
1275 for(Q=0; Q<WLUT_WIDTH; Q++)
1276 resample_filter->filter_lut[Q] = (double)
1277 GetResizeFilterWeight(resize_filter,sqrt((double)Q)*r_scale);
1279 /* finished with the resize filter */
1280 resize_filter = DestroyResizeFilter(resize_filter);
1283 /* save the filter and the scaled ellipse bounds needed for filter */
1284 resample_filter->filter_def = resize_filter;
1285 resample_filter->F = resample_filter->support*resample_filter->support;
1289 Adjust the scaling of the default unit circle
1290 This assumes that any real scaling changes will always
1291 take place AFTER the filter method has been initialized.
1293 ScaleResampleFilter(resample_filter, 1.0, 0.0, 0.0, 1.0);
1296 /* This is old code kept as a reference only. It is very wrong,
1297 and I don't understand exactly what it was attempting to do.
1300 Create Normal Gaussian 2D Filter Weighted Lookup Table.
1301 A normal EWA guassual lookup would use exp(Q*ALPHA)
1302 where Q = distance squared from 0.0 (center) to 1.0 (edge)
1303 and ALPHA = -4.0*ln(2.0) ==> -2.77258872223978123767
1304 The table is of length 1024, and equates to support radius of 2.0
1305 thus needs to be scaled by ALPHA*4/1024 and any blur factor squared
1307 The above came from some reference code provided by Fred Weinhaus
1308 and seems to have been a guess that was appropriate for its use
1309 in a 3d perspective landscape mapping program.
1311 r_scale = -2.77258872223978123767/(WLUT_WIDTH*blur*blur);
1312 for(Q=0; Q<WLUT_WIDTH; Q++)
1313 resample_filter->filter_lut[Q] = exp((double)Q*r_scale);
1314 resample_filter->support = WLUT_WIDTH;
1319 #if defined(MAGICKCORE_OPENMP_SUPPORT)
1327 /* Scale radius so the filter LUT covers the full support range */
1328 r_scale = resample_filter->support*sqrt(1.0/(double)WLUT_WIDTH);
1329 if (IfTrue(IsStringTrue(GetImageArtifact(resample_filter->image,
1330 "resample:verbose"))) )
1332 /* Debug output of the filter weighting LUT
1333 Gnuplot the LUT with hoizontal adjusted to 'r' using...
1334 plot [0:2][-.2:1] "lut.dat" using (sqrt($0/1024)*2):1 with lines
1335 The filter values is normalized for comparision
1338 printf("# Resampling Filter LUT (%d values)\n", WLUT_WIDTH);
1340 printf("# Note: values in table are using a squared radius lookup.\n");
1341 printf("# And the whole table represents the filters support.\n");
1342 printf("\n"); /* generates a 'break' in gnuplot if multiple outputs */
1343 for(Q=0; Q<WLUT_WIDTH; Q++)
1344 printf("%8.*g %.*g\n",
1345 GetMagickPrecision(),sqrt((double)Q)*r_scale,
1346 GetMagickPrecision(),resample_filter->filter_lut[Q] );
1348 /* output the above once only for each image, and each setting */
1349 (void) DeleteImageArtifact(resample_filter->image,"resample:verbose");
1351 #endif /* FILTER_LUT */
1356 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1360 % 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 %
1364 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1366 % SetResampleFilterInterpolateMethod() sets the resample filter interpolation
1369 % The format of the SetResampleFilterInterpolateMethod method is:
1371 % MagickBooleanType SetResampleFilterInterpolateMethod(
1372 % ResampleFilter *resample_filter,const InterpolateMethod method)
1374 % A description of each parameter follows:
1376 % o resample_filter: the resample filter.
1378 % o method: the interpolation method.
1381 MagickExport MagickBooleanType SetResampleFilterInterpolateMethod(
1382 ResampleFilter *resample_filter,const PixelInterpolateMethod method)
1384 assert(resample_filter != (ResampleFilter *) NULL);
1385 assert(resample_filter->signature == MagickSignature);
1386 assert(resample_filter->image != (Image *) NULL);
1387 if (resample_filter->debug != MagickFalse)
1388 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
1389 resample_filter->image->filename);
1390 resample_filter->interpolate=method;
1395 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1399 % 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 %
1403 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
1405 % SetResampleFilterVirtualPixelMethod() changes the virtual pixel method
1406 % associated with the specified resample filter.
1408 % The format of the SetResampleFilterVirtualPixelMethod method is:
1410 % MagickBooleanType SetResampleFilterVirtualPixelMethod(
1411 % ResampleFilter *resample_filter,const VirtualPixelMethod method)
1413 % A description of each parameter follows:
1415 % o resample_filter: the resample filter.
1417 % o method: the virtual pixel method.
1420 MagickExport MagickBooleanType SetResampleFilterVirtualPixelMethod(
1421 ResampleFilter *resample_filter,const VirtualPixelMethod method)
1423 assert(resample_filter != (ResampleFilter *) NULL);
1424 assert(resample_filter->signature == MagickSignature);
1425 assert(resample_filter->image != (Image *) NULL);
1426 if (resample_filter->debug != MagickFalse)
1427 (void) LogMagickEvent(TraceEvent,GetMagickModule(),"%s",
1428 resample_filter->image->filename);
1429 resample_filter->virtual_pixel=method;
1430 if (method != UndefinedVirtualPixelMethod)
1431 (void) SetCacheViewVirtualPixelMethod(resample_filter->view,method);