mirror of
https://github.com/python-pillow/Pillow.git
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326 lines
9.8 KiB
C
326 lines
9.8 KiB
C
/*
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* The Python Imaging Library
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* $Id$
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*
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* Pillow image resampling support
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*
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* history:
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* 2002-03-09 fl Created (for PIL 1.1.3)
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* 2002-03-10 fl Added support for mode "F"
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*
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* Copyright (c) 1997-2002 by Secret Labs AB
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*
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* See the README file for information on usage and redistribution.
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*/
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#include "Imaging.h"
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#include <math.h>
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struct filter {
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float (*filter)(float x);
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float support;
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};
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static inline float sinc_filter(float x)
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{
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if (x == 0.0)
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return 1.0;
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x = x * M_PI;
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return sin(x) / x;
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}
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static inline float lanczos_filter(float x)
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{
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/* truncated sinc */
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if (-3.0 <= x && x < 3.0)
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return sinc_filter(x) * sinc_filter(x/3);
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return 0.0;
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}
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static inline float bilinear_filter(float x)
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{
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if (x < 0.0)
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x = -x;
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if (x < 1.0)
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return 1.0-x;
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return 0.0;
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}
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static inline float bicubic_filter(float x)
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{
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/* https://en.wikipedia.org/wiki/Bicubic_interpolation#Bicubic_convolution_algorithm */
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#define a -0.5
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if (x < 0.0)
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x = -x;
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if (x < 1.0)
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return ((a + 2.0) * x - (a + 3.0)) * x*x + 1;
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if (x < 2.0)
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return (((x - 5) * x + 8) * x - 4) * a;
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return 0.0;
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#undef a
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}
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static struct filter LANCZOS = { lanczos_filter, 3.0 };
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static struct filter BILINEAR = { bilinear_filter, 1.0 };
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static struct filter BICUBIC = { bicubic_filter, 2.0 };
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/* 8 bits for result. Filter can have negative areas.
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In one cases the sum of the coefficients will be negative,
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in the other it will be more than 1.0. That is why we need
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two extra bits for overflow and int type. */
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#define PRECISION_BITS (32 - 8 - 2)
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static inline UINT8 clip8(int in)
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{
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if (in >= (1 << PRECISION_BITS << 8))
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return 255;
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if (in <= 0)
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return 0;
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return (UINT8) (in >> PRECISION_BITS);
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}
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Imaging
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ImagingResampleHorizontal(Imaging imIn, int xsize, struct filter *filterp)
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{
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ImagingSectionCookie cookie;
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Imaging imOut;
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float support, scale, filterscale;
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float center, ww, ss;
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int ss0, ss1, ss2, ss3;
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int xx, yy, x, kmax, xmin, xmax;
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int *xbounds;
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int *k, *kk;
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float *kw;
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/* prepare for horizontal stretch */
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filterscale = scale = (float) imIn->xsize / xsize;
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if (filterscale < 1.0) {
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filterscale = 1.0;
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}
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/* determine support size (length of resampling filter) */
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support = filterp->support * filterscale;
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/* maximum number of coofs */
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kmax = (int) ceil(support) * 2 + 1;
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// check for overflow
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if (xsize > SIZE_MAX / (kmax * sizeof(int)))
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return (Imaging) ImagingError_MemoryError();
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// sizeof(int) should be greater than 0 as well
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if (xsize > SIZE_MAX / (2 * sizeof(int)))
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return (Imaging) ImagingError_MemoryError();
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/* coefficient buffer */
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kk = malloc(xsize * kmax * sizeof(int));
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if ( ! kk)
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return (Imaging) ImagingError_MemoryError();
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/* intermediate not normalized buffer for coefficients */
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kw = malloc(kmax * sizeof(float));
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if ( ! kw) {
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free(kk);
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return (Imaging) ImagingError_MemoryError();
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}
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xbounds = malloc(xsize * 2 * sizeof(int));
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if ( ! xbounds) {
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free(kk);
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free(kw);
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return (Imaging) ImagingError_MemoryError();
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}
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for (xx = 0; xx < xsize; xx++) {
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center = (xx + 0.5) * scale;
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ww = 0.0;
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ss = 1.0 / filterscale;
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xmin = (int) floor(center - support);
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if (xmin < 0)
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xmin = 0;
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xmax = (int) ceil(center + support);
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if (xmax > imIn->xsize)
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xmax = imIn->xsize;
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for (x = xmin; x < xmax; x++) {
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float w = filterp->filter((x - center + 0.5) * ss);
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kw[x - xmin] = w;
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ww += w;
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}
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k = &kk[xx * kmax];
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for (x = 0; x < xmax - xmin; x++) {
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if (ww != 0.0)
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k[x] = (int) floor(0.5 + kw[x] / ww * (1 << PRECISION_BITS));
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}
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xbounds[xx * 2 + 0] = xmin;
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xbounds[xx * 2 + 1] = xmax;
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}
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free(kw);
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imOut = ImagingNew(imIn->mode, xsize, imIn->ysize);
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if ( ! imOut) {
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free(kk);
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free(xbounds);
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return NULL;
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}
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ImagingSectionEnter(&cookie);
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/* horizontal stretch */
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for (yy = 0; yy < imOut->ysize; yy++) {
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if (imIn->image8) {
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/* 8-bit grayscale */
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss0 = 1 << (PRECISION_BITS -1);
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for (x = xmin; x < xmax; x++)
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ss0 += ((UINT8) imIn->image8[yy][x]) * k[x - xmin];
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imOut->image8[yy][xx] = clip8(ss0);
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}
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} else {
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switch(imIn->type) {
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case IMAGING_TYPE_UINT8:
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/* n-bit grayscale */
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if (imIn->bands == 2) {
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss0 = ss1 = 1 << (PRECISION_BITS -1);
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for (x = xmin; x < xmax; x++) {
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ss0 += ((UINT8) imIn->image[yy][x*4 + 0]) * k[x - xmin];
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ss1 += ((UINT8) imIn->image[yy][x*4 + 3]) * k[x - xmin];
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}
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imOut->image[yy][xx*4 + 0] = clip8(ss0);
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imOut->image[yy][xx*4 + 3] = clip8(ss1);
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}
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} else if (imIn->bands == 3) {
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss0 = ss1 = ss2 = 1 << (PRECISION_BITS -1);
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for (x = xmin; x < xmax; x++) {
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ss0 += ((UINT8) imIn->image[yy][x*4 + 0]) * k[x - xmin];
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ss1 += ((UINT8) imIn->image[yy][x*4 + 1]) * k[x - xmin];
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ss2 += ((UINT8) imIn->image[yy][x*4 + 2]) * k[x - xmin];
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}
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imOut->image[yy][xx*4 + 0] = clip8(ss0);
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imOut->image[yy][xx*4 + 1] = clip8(ss1);
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imOut->image[yy][xx*4 + 2] = clip8(ss2);
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}
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} else {
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss0 = ss1 = ss2 = ss3 = 1 << (PRECISION_BITS -1);
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for (x = xmin; x < xmax; x++) {
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ss0 += ((UINT8) imIn->image[yy][x*4 + 0]) * k[x - xmin];
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ss1 += ((UINT8) imIn->image[yy][x*4 + 1]) * k[x - xmin];
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ss2 += ((UINT8) imIn->image[yy][x*4 + 2]) * k[x - xmin];
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ss3 += ((UINT8) imIn->image[yy][x*4 + 3]) * k[x - xmin];
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}
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imOut->image[yy][xx*4 + 0] = clip8(ss0);
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imOut->image[yy][xx*4 + 1] = clip8(ss1);
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imOut->image[yy][xx*4 + 2] = clip8(ss2);
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imOut->image[yy][xx*4 + 3] = clip8(ss3);
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}
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}
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break;
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case IMAGING_TYPE_INT32:
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/* 32-bit integer */
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss = 0.0;
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for (x = xmin; x < xmax; x++)
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ss += (IMAGING_PIXEL_I(imIn, x, yy)) * k[x - xmin];
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IMAGING_PIXEL_I(imOut, xx, yy) = (int) ss;
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}
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break;
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case IMAGING_TYPE_FLOAT32:
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/* 32-bit float */
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for (xx = 0; xx < xsize; xx++) {
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xmin = xbounds[xx * 2 + 0];
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xmax = xbounds[xx * 2 + 1];
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k = &kk[xx * kmax];
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ss = 0.0;
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for (x = xmin; x < xmax; x++)
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ss += IMAGING_PIXEL_F(imIn, x, yy) * k[x - xmin];
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IMAGING_PIXEL_F(imOut, xx, yy) = ss;
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}
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break;
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}
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}
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}
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ImagingSectionLeave(&cookie);
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free(kk);
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free(xbounds);
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return imOut;
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}
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Imaging
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ImagingResample(Imaging imIn, int xsize, int ysize, int filter)
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{
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Imaging imTemp1, imTemp2, imTemp3;
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Imaging imOut;
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struct filter *filterp;
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if (strcmp(imIn->mode, "P") == 0 || strcmp(imIn->mode, "1") == 0)
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return (Imaging) ImagingError_ModeError();
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if (imIn->type == IMAGING_TYPE_SPECIAL)
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return (Imaging) ImagingError_ModeError();
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/* check filter */
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switch (filter) {
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case IMAGING_TRANSFORM_LANCZOS:
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filterp = &LANCZOS;
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break;
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case IMAGING_TRANSFORM_BILINEAR:
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filterp = &BILINEAR;
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break;
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case IMAGING_TRANSFORM_BICUBIC:
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filterp = &BICUBIC;
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break;
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default:
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return (Imaging) ImagingError_ValueError(
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"unsupported resampling filter"
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);
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}
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/* two-pass resize, first pass */
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imTemp1 = ImagingResampleHorizontal(imIn, xsize, filterp);
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if ( ! imTemp1)
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return NULL;
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/* transpose image once */
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imTemp2 = ImagingTransposeToNew(imTemp1);
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ImagingDelete(imTemp1);
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if ( ! imTemp2)
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return NULL;
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/* second pass */
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imTemp3 = ImagingResampleHorizontal(imTemp2, ysize, filterp);
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ImagingDelete(imTemp2);
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if ( ! imTemp3)
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return NULL;
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/* transpose result */
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imOut = ImagingTransposeToNew(imTemp3);
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ImagingDelete(imTemp3);
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if ( ! imOut)
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return NULL;
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return imOut;
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}
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