![[tokkee]](http://tokkee.org/images/avatar.png){kind=avatar}
index ccbc018ef84b09da0e1b73aa4dd290b6536c54dc..5ef43039475e1570cb7c745693270805e98d3d79 100644 (file)
#include <cmath>
#include <complex>
#include <glib.h>
+#include <cstdlib>
#include <limits>
#include "isnan.h"
#include "display/nr-filter-primitive.h"
#include "display/nr-filter-gaussian.h"
#include "display/nr-filter-types.h"
+#include "display/nr-filter-units.h"
#include "libnr/nr-pixblock.h"
#include "libnr/nr-matrix.h"
+#include "libnr/nr-matrix-fns.h"
#include "util/fixed_point.h"
#include "prefs-utils.h"
// Using the backwards-pass initialization procedure from:
// Boundary Conditions for Young - van Vliet Recursive Filtering
// Bill Triggs, Michael Sdika
-// IEEE Transactions on Signal Processing, Volume 54, Number 5 - may 2006
+// IEEE Transactions on Signal Processing, Volume 54, Number 5 - may 2006
// Number of IIR filter coefficients used. Currently only 3 is supported.
// "Recursive Gaussian Derivative Filters" says this is enough though (and
// some testing indeed shows that the quality doesn't improve much if larger
// filters are used).
-const size_t N = 3;
+static size_t const N = 3;
template<typename InIt, typename OutIt, typename Size>
void copy_n(InIt beg_in, Size N, OutIt beg_out) {
}
// Type used for IIR filter coefficients (can be 10.21 signed fixed point, see Anisotropic Gaussian Filtering Using Fixed Point Arithmetic, Christoph H. Lampert & Oliver Wirjadi, 2006)
-typedef double IIRValue;
+typedef double IIRValue;
// Type used for FIR filter coefficients (can be 16.16 unsigned fixed point, should have 8 or more bits in the fractional part, the integer part should be capable of storing approximately 20*255)
typedef Inkscape::Util::FixedPoint<unsigned int,16> FIRValue;
template<typename Tt, typename Ts>
static inline Tt round_cast(Ts const& v) {
- static Ts const rndoffset(.5);
- return static_cast<Tt>(v+rndoffset);
+ static Ts const rndoffset(.5);
+ return static_cast<Tt>(v+rndoffset);
}
template<typename Tt, typename Ts>
static inline Tt clip_round_cast(Ts const& v, Tt const minval=std::numeric_limits<Tt>::min(), Tt const maxval=std::numeric_limits<Tt>::max()) {
if ( v < minval ) return minval;
if ( v > maxval ) return maxval;
- return round_cast<Tt>(v);
+ return round_cast<Tt>(v);
}
namespace NR {
// Nothing to do here
}
-int _effect_area_scr(double deviation)
+static int
+_effect_area_scr(double const deviation)
{
return (int)std::ceil(deviation * 3.0);
}
-void _make_kernel(FIRValue *kernel, double deviation)
+static void
+_make_kernel(FIRValue *const kernel, double const deviation)
{
int const scr_len = _effect_area_scr(deviation);
double const d_sq = sqr(deviation) * 2;
// 8<=32-2*v
// 2*v<=24
// v<=12
-int _effect_subsample_step_log2(double deviation, int quality)
+static int
+_effect_subsample_step_log2(double const deviation, int const quality)
{
// To make sure FIR will always be used (unless the kernel is VERY big):
// deviation/step <= 3
* Catches reading and writing outside the pixblock area.
* When enabled, decreases filter rendering speed massively.
*/
-inline void _check_index(NRPixBlock const * const pb, int const location, int const line)
+static inline void
+_check_index(NRPixBlock const * const pb, int const location, int const line)
{
if (false) {
int max_loc = pb->rs * (pb->area.y1 - pb->area.y0);
@@ -257,7 +264,12 @@ static void calcTriggsSdikaInitialization(double const M[N*N], IIRValue const uo
// Filters over 1st dimension
template<typename PT, unsigned int PC, bool PREMULTIPLIED_ALPHA>
-void filter2D_IIR(PT *dest, int dstr1, int dstr2, PT const *src, int sstr1, int sstr2, int n1, int n2, IIRValue const b[N+1], double const M[N*N], IIRValue *const tmpdata) {
+static void
+filter2D_IIR(PT *const dest, int const dstr1, int const dstr2,
+ PT const *const src, int const sstr1, int const sstr2,
+ int const n1, int const n2, IIRValue const b[N+1], double const M[N*N],
+ IIRValue *const tmpdata)
+{
for ( int c2 = 0 ; c2 < n2 ; c2++ ) {
// corresponding line in the source and output buffer
PT const * srcimg = src + c2*sstr2;
@@ -311,7 +323,11 @@ void filter2D_IIR(PT *dest, int dstr1, int dstr2, PT const *src, int sstr1, int
// Assumes kernel is symmetric
// scr_len should be size of kernel - 1
template<typename PT, unsigned int PC>
-void filter2D_FIR(PT *dst, int dstr1, int dstr2, PT const *src, int sstr1, int sstr2, int n1, int n2, FIRValue const *const kernel, int scr_len) {
+static void
+filter2D_FIR(PT *const dst, int const dstr1, int const dstr2,
+ PT const *const src, int const sstr1, int const sstr2,
+ int const n1, int const n2, FIRValue const *const kernel, int const scr_len)
+{
// Past pixels seen (to enable in-place operation)
PT history[scr_len+1][PC];
@@ -385,8 +401,8 @@ void filter2D_FIR(PT *dst, int dstr1, int dstr2, PT const *src, int sstr1, int s
// store the result in bufx
dst[dst_disp + byte] = round_cast<PT>(sum);
- // optimization: if there was no variation within this point's neighborhood,
- // skip ahead while we keep seeing the same last_in byte:
+ // optimization: if there was no variation within this point's neighborhood,
+ // skip ahead while we keep seeing the same last_in byte:
// blurring flat color would not change it anyway
if (different_count <= 1) {
int pos = c1 + 1;
@@ -406,7 +422,11 @@ void filter2D_FIR(PT *dst, int dstr1, int dstr2, PT const *src, int sstr1, int s
}
template<typename PT, unsigned int PC>
-void downsample(PT *dst, int dstr1, int dstr2, int dn1, int dn2, PT const *src, int sstr1, int sstr2, int sn1, int sn2, int step1_l2, int step2_l2) {
+static void
+downsample(PT *const dst, int const dstr1, int const dstr2, int const dn1, int const dn2,
+ PT const *const src, int const sstr1, int const sstr2, int const sn1, int const sn2,
+ int const step1_l2, int const step2_l2)
+{
unsigned int const divisor_l2 = step1_l2+step2_l2; // step1*step2=2^(step1_l2+step2_l2)
unsigned int const round_offset = (1<<divisor_l2)/2;
int const step1 = 1<<step1_l2;
@@ -436,7 +456,11 @@ void downsample(PT *dst, int dstr1, int dstr2, int dn1, int dn2, PT const *src,
}
template<typename PT, unsigned int PC>
-void upsample(PT *dst, int dstr1, int dstr2, unsigned int dn1, unsigned int dn2, PT const *src, int sstr1, int sstr2, unsigned int sn1, unsigned int sn2, unsigned int step1_l2, unsigned int step2_l2) {
+static void
+upsample(PT *const dst, int const dstr1, int const dstr2, unsigned int const dn1, unsigned int const dn2,
+ PT const *const src, int const sstr1, int const sstr2, unsigned int const sn1, unsigned int const sn2,
+ unsigned int const step1_l2, unsigned int const step2_l2)
+{
assert(((sn1-1)<<step1_l2)>=dn1 && ((sn2-1)<<step2_l2)>=dn2); // The last pixel of the source image should fall outside the destination image
unsigned int const divisor_l2 = step1_l2+step2_l2; // step1*step2=2^(step1_l2+step2_l2)
unsigned int const round_offset = (1<<divisor_l2)/2;
@@ -484,10 +508,16 @@ void upsample(PT *dst, int dstr1, int dstr2, unsigned int dn1, unsigned int dn2,
}
}
-int FilterGaussian::render(FilterSlot &slot, Matrix const &trans)
+int FilterGaussian::render(FilterSlot &slot, FilterUnits const &units)
{
/* in holds the input pixblock */
NRPixBlock *in = slot.get(_input);
+ if (!in) {
+ g_warning("Missing source image for feGaussianBlur (in=%d)", _input);
+ return 1;
+ }
+
+ Matrix trans = units.get_matrix_primitiveunits2pb();
/* If to either direction, the standard deviation is zero or
* input image is not defined,
// Some common constants
int const width_org = in->area.x1-in->area.x0, height_org = in->area.y1-in->area.y0;
- double const deviation_x_org = _deviation_x * trans.expansionX();
- double const deviation_y_org = _deviation_y * trans.expansionY();
+ double const deviation_x_org = _deviation_x * NR::expansionX(trans);
+ double const deviation_y_org = _deviation_y * NR::expansionY(trans);
int const PC = NR_PIXBLOCK_BPP(in);
// Subsampling constants
void FilterGaussian::area_enlarge(NRRectL &area, Matrix const &trans)
{
- int area_x = _effect_area_scr(_deviation_x * trans.expansionX());
- int area_y = _effect_area_scr(_deviation_y * trans.expansionY());
+ int area_x = _effect_area_scr(_deviation_x * NR::expansionX(trans));
+ int area_y = _effect_area_scr(_deviation_y * NR::expansionY(trans));
// maximum is used because rotations can mix up these directions
// TODO: calculate a more tight-fitting rendering area
int area_max = std::max(area_x, area_y);
area.y1 += area_max;
}
+FilterTraits FilterGaussian::get_input_traits() {
+ return TRAIT_PARALLER;
+}
+
void FilterGaussian::set_deviation(double deviation)
{
if(isFinite(deviation) && deviation >= 0) {