mirror-github-bspeice/flam3
1
0
Fork 0
mirror of https://github.com/scottdraves/flam3.git synced 2025-01-21 05:20:05 -05:00
Code Issues Actions Packages Projects Releases Wiki Activity
be1b9278b6
flam3/filters.c

491 lines
14 KiB
C
Raw Blame History

/*
FLAM3 - cosmic recursive fractal flames
Copyright (C) 1992-2009 Spotworks LLC
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
#include "filters.h"
/*
* filter function definitions
* from Graphics Gems III code
* and ImageMagick resize.c
*/
double flam3_spatial_support[flam3_num_spatialfilters] = {
1.5, /* gaussian */
1.0, /* hermite */
0.5, /* box */
1.0, /* triangle */
1.5, /* bell */
2.0, /* b spline */
2.0, /* mitchell */
1.0, /* blackman */
2.0, /* catrom */
1.0, /* hanning */
1.0, /* hamming */
3.0, /* lanczos3 */
2.0, /* lanczos2 */
1.5 /* quadratic */
};
double flam3_hermite_filter(double t) {
/* f(t) = 2|t|^3 - 3|t|^2 + 1, -1 <= t <= 1 */
if(t < 0.0) t = -t;
if(t < 1.0) return((2.0 * t - 3.0) * t * t + 1.0);
return(0.0);
}
double flam3_box_filter(double t) {
if((t > -0.5) && (t <= 0.5)) return(1.0);
return(0.0);
}
double flam3_triangle_filter(double t) {
if(t < 0.0) t = -t;
if(t < 1.0) return(1.0 - t);
return(0.0);
}
double flam3_bell_filter(double t) {
/* box (*) box (*) box */
if(t < 0) t = -t;
if(t < .5) return(.75 - (t * t));
if(t < 1.5) {
t = (t - 1.5);
return(.5 * (t * t));
}
return(0.0);
}
double flam3_b_spline_filter(double t) {
/* box (*) box (*) box (*) box */
double tt;
if(t < 0) t = -t;
if(t < 1) {
tt = t * t;
return((.5 * tt * t) - tt + (2.0 / 3.0));
} else if(t < 2) {
t = 2 - t;
return((1.0 / 6.0) * (t * t * t));
}
return(0.0);
}
double flam3_sinc(double x) {
x *= M_PI;
if(x != 0) return(sin(x) / x);
return(1.0);
}
double flam3_blackman_filter(double x) {
return(0.42+0.5*cos(M_PI*x)+0.08*cos(2*M_PI*x));
}
double flam3_catrom_filter(double x) {
if (x < -2.0)
return(0.0);
if (x < -1.0)
return(0.5*(4.0+x*(8.0+x*(5.0+x))));
if (x < 0.0)
return(0.5*(2.0+x*x*(-5.0-3.0*x)));
if (x < 1.0)
return(0.5*(2.0+x*x*(-5.0+3.0*x)));
if (x < 2.0)
return(0.5*(4.0+x*(-8.0+x*(5.0-x))));
return(0.0);
}
double flam3_mitchell_filter(double t) {
double tt;
tt = t * t;
if(t < 0) t = -t;
if(t < 1.0) {
t = (((12.0 - 9.0 * flam3_mitchell_b - 6.0 * flam3_mitchell_c) * (t * tt))
+ ((-18.0 + 12.0 * flam3_mitchell_b + 6.0 * flam3_mitchell_c) * tt)
+ (6.0 - 2 * flam3_mitchell_b));
return(t / 6.0);
} else if(t < 2.0) {
t = (((-1.0 * flam3_mitchell_b - 6.0 * flam3_mitchell_c) * (t * tt))
+ ((6.0 * flam3_mitchell_b + 30.0 * flam3_mitchell_c) * tt)
+ ((-12.0 * flam3_mitchell_b - 48.0 * flam3_mitchell_c) * t)
+ (8.0 * flam3_mitchell_b + 24 * flam3_mitchell_c));
return(t / 6.0);
}
return(0.0);
}
double flam3_hanning_filter(double x) {
return(0.5+0.5*cos(M_PI*x));
}
double flam3_hamming_filter(double x) {
return(0.54+0.46*cos(M_PI*x));
}
double flam3_lanczos3_filter(double t) {
if(t < 0) t = -t;
if(t < 3.0) return(flam3_sinc(t) * flam3_sinc(t/3.0));
return(0.0);
}
double flam3_lanczos2_filter(double t) {
if(t < 0) t = -t;
if(t < 2.0) return(flam3_sinc(t) * flam3_sinc(t/2.0));
return(0.0);
}
double flam3_gaussian_filter(double x) {
return(exp((-2.0*x*x))*sqrt(2.0/M_PI));
}
double flam3_quadratic_filter(double x) {
if (x < -1.5)
return(0.0);
if (x < -0.5)
return(0.5*(x+1.5)*(x+1.5));
if (x < 0.5)
return(0.75-x*x);
if (x < 1.5)
return(0.5*(x-1.5)*(x-1.5));
return(0.0);
}
double flam3_spatial_filter(int knum, double x) {
if (knum==0)
return flam3_gaussian_filter(x);
else if (knum==1)
return flam3_hermite_filter(x);
else if (knum==2)
return flam3_box_filter(x);
else if (knum==3)
return flam3_triangle_filter(x);
else if (knum==4)
return flam3_bell_filter(x);
else if (knum==5)
return flam3_b_spline_filter(x);
else if (knum==6)
return flam3_mitchell_filter(x);
else if (knum==7)
return flam3_sinc(x)*flam3_blackman_filter(x);
else if (knum==8)
return flam3_catrom_filter(x);
else if (knum==9)
return flam3_sinc(x)*flam3_hanning_filter(x);
else if (knum==10)
return flam3_sinc(x)*flam3_hamming_filter(x);
else if (knum==11)
return flam3_lanczos3_filter(x)*flam3_sinc(x/3.0);
else if (knum==12)
return flam3_lanczos2_filter(x)*flam3_sinc(x/2.0);
else // if (knum==13)
return flam3_quadratic_filter(x);
}
int normalize_vector(double *v, int n) {
double t = 0.0;
int i;
for (i = 0; i < n; i++)
t += v[i];
if (0.0 == t) return 1;
t = 1.0 / t;
for (i = 0; i < n; i++)
v[i] *= t;
return 0;
}
int flam3_create_spatial_filter(flam3_frame *spec, int field, double **filter) {
int sf_kernel = spec->genomes[0].spatial_filter_select;
int supersample = spec->genomes[0].spatial_oversample;
double sf_radius = spec->genomes[0].spatial_filter_radius;
double aspect_ratio = spec->pixel_aspect_ratio;
double sf_supp = flam3_spatial_support[sf_kernel];
double fw = 2.0 * sf_supp * supersample * sf_radius / aspect_ratio;
double adjust, ii, jj;
int fwidth = ((int) fw) + 1;
int i,j;
/* Make sure the filter kernel has same parity as oversample */
if ((fwidth ^ supersample) & 1)
fwidth++;
/* Calculate the coordinate scaling factor for the kernel values */
if (fw > 0.0)
adjust = sf_supp * fwidth / fw;
else
adjust = 1.0;
/* Calling function MUST FREE THE RETURNED KERNEL, lest ye leak memory */
(*filter) = (double *)calloc(fwidth * fwidth,sizeof(double));
/* fill in the coefs */
for (i = 0; i < fwidth; i++)
for (j = 0; j < fwidth; j++) {
/* Calculate the function inputs for the kernel function */
ii = ((2.0 * i + 1.0) / (double)fwidth - 1.0)*adjust;
jj = ((2.0 * j + 1.0) / (double)fwidth - 1.0)*adjust;
/* Scale for scanlines */
if (field) jj *= 2.0;
/* Adjust for aspect ratio */
jj /= aspect_ratio;
(*filter)[i + j * fwidth] =
flam3_spatial_filter(sf_kernel,ii) * flam3_spatial_filter(sf_kernel,jj);
}
if (normalize_vector((*filter), fwidth * fwidth)) {
fprintf(stderr, "Spatial filter value is too small: %g. Terminating.\n",sf_radius);
return(-1);
}
return (fwidth);
}
flam3_de_helper flam3_create_de_filters(double max_rad, double min_rad, double curve, int ss) {
flam3_de_helper de;
double comp_max_radius, comp_min_radius;
double num_de_filters_d;
int num_de_filters,de_max_ind;
int de_row_size, de_half_size;
int filtloop;
int keep_thresh=100;
de.kernel_size=-1;
if (curve <= 0.0) {
fprintf(stderr,"estimator curve must be > 0\n");
return(de);
}
if (max_rad < min_rad) {
fprintf(stderr,"estimator must be larger than estimator_minimum.\n");
fprintf(stderr,"(%f > %f) ? \n",max_rad,min_rad);
return(de);
}
/* We should scale the filter width by the oversample */
/* The '+1' comes from the assumed distance to the first pixel */
comp_max_radius = max_rad*ss + 1;
comp_min_radius = min_rad*ss + 1;
/* Calculate how many filter kernels we need based on the decay function */
/* */
/* num filters = (de_max_width / de_min_width)^(1/estimator_curve) */
/* */
num_de_filters_d = pow( comp_max_radius/comp_min_radius, 1.0/curve );
if (num_de_filters_d>1e7) {
fprintf(stderr,"too many filters required in this configuration (%g)\n",num_de_filters_d);
return(de);
}
num_de_filters = (int)ceil(num_de_filters_d);
/* Condense the smaller kernels to save space */
if (num_de_filters>keep_thresh) {
de_max_ind = (int)ceil(DE_THRESH + pow(num_de_filters-DE_THRESH,curve))+1;
de.max_filtered_counts = (int)pow( (double)(de_max_ind-DE_THRESH), 1.0/curve) + DE_THRESH;
} else {
de_max_ind = num_de_filters;
de.max_filtered_counts = de_max_ind;
}
/* Allocate the memory for these filters */
/* and the hit/width lookup vector */
de_row_size = (int)(2*ceil(comp_max_radius)-1);
de_half_size = (de_row_size-1)/2;
de.kernel_size = (de_half_size+1)*(2+de_half_size)/2;
de.filter_coefs = (double *) calloc (de_max_ind * de.kernel_size,sizeof(double));
de.filter_widths = (double *) calloc (de_max_ind,sizeof(double));
/* Generate the filter coefficients */
de.max_filter_index = 0;
for (filtloop=0;filtloop<de_max_ind;filtloop++) {
double de_filt_sum=0.0, de_filt_d;
double de_filt_h;
int dej,dek;
double adjloop;
int filter_coef_idx;
/* Calculate the filter width for this number of hits in a bin */
if (filtloop<keep_thresh)
de_filt_h = (comp_max_radius / pow(filtloop+1,curve));
else {
adjloop = pow(filtloop-keep_thresh,(1.0/curve)) + keep_thresh;
de_filt_h = (comp_max_radius / pow(adjloop+1,curve));
}
/* Once we've reached the min radius, don't populate any more */
if (de_filt_h <= comp_min_radius) {
de_filt_h = comp_min_radius;
de.max_filter_index = filtloop;
}
de.filter_widths[filtloop] = de_filt_h;
/* Calculate norm of kernel separately (easier) */
for (dej=-de_half_size; dej<=de_half_size; dej++) {
for (dek=-de_half_size; dek<=de_half_size; dek++) {
de_filt_d = sqrt( (double)(dej*dej+dek*dek) ) / de_filt_h;
/* Only populate the coefs within this radius */
if (de_filt_d <= 1.0) {
/* Gaussian */
de_filt_sum += flam3_spatial_filter(flam3_gaussian_kernel,
flam3_spatial_support[flam3_gaussian_kernel]*de_filt_d);
/* Epanichnikov */
// de_filt_sum += (1.0 - (de_filt_d * de_filt_d));
}
}
}
filter_coef_idx = filtloop*de.kernel_size;
/* Calculate the unique entries of the kernel */
for (dej=0; dej<=de_half_size; dej++) {
for (dek=0; dek<=dej; dek++) {
de_filt_d = sqrt( (double)(dej*dej+dek*dek) ) / de_filt_h;
/* Only populate the coefs within this radius */
if (de_filt_d>1.0)
de.filter_coefs[filter_coef_idx] = 0.0;
else {
/* Gaussian */
de.filter_coefs[filter_coef_idx] = flam3_spatial_filter(flam3_gaussian_kernel,
flam3_spatial_support[flam3_gaussian_kernel]*de_filt_d)/de_filt_sum;
/* Epanichnikov */
// de_filter_coefs[filter_coef_idx] = (1.0 - (de_filt_d * de_filt_d))/de_filt_sum;
}
filter_coef_idx ++;
}
}
if (de.max_filter_index>0)
break;
}
if (de.max_filter_index==0)
de.max_filter_index = de_max_ind-1;
return(de);
}
double flam3_create_temporal_filter(int numsteps, int filter_type, double filter_exp, double filter_width,
double **temporal_filter, double **temporal_deltas) {
double maxfilt = 0.0;
double sumfilt = 0.0;
double slpx,halfsteps;
double *deltas, *filter;
int i;
/* Allocate memory - this must be freed in the calling routine! */
deltas = (double *)malloc(numsteps*sizeof(double));
filter = (double *)malloc(numsteps*sizeof(double));
/* Deal with only one step */
if (numsteps==1) {
deltas[0] = 0;
filter[0] = 1.0;
*temporal_deltas = deltas;
*temporal_filter = filter;
return(1.0);
}
/* Define the temporal deltas */
for (i = 0; i < numsteps; i++)
deltas[i] = ((double)i /(double)(numsteps - 1) - 0.5)*filter_width;
/* Define the filter coefs */
if (flam3_temporal_exp == filter_type) {
for (i=0; i < numsteps; i++) {
if (filter_exp>=0)
slpx = ((double)i+1.0)/numsteps;
else
slpx = (double)(numsteps - i)/numsteps;
/* Scale the color based on these values */
filter[i] = pow(slpx,fabs(filter_exp));
/* Keep the max */
if (filter[i]>maxfilt)
maxfilt = filter[i];
}
} else if (flam3_temporal_gaussian == filter_type) {
halfsteps = numsteps/2.0;
for (i=0; i < numsteps; i++) {
/* Gaussian */
filter[i] = flam3_spatial_filter(flam3_gaussian_kernel,
flam3_spatial_support[flam3_gaussian_kernel]*fabs(i - halfsteps)/halfsteps);
/* Keep the max */
if (filter[i]>maxfilt)
maxfilt = filter[i];
}
} else { // (flam3_temporal_box)
for (i=0; i < numsteps; i++)
filter[i] = 1.0;
maxfilt = 1.0;
}
/* Adjust the filter so that the max is 1.0, and */
/* calculate the K2 scaling factor */
for (i=0;i<numsteps;i++) {
filter[i] /= maxfilt;
sumfilt += filter[i];
}
sumfilt /= numsteps;
*temporal_deltas = deltas;
*temporal_filter = filter;
return(sumfilt);
}
Reference in New Issue View Git Blame Copy Permalink