1292 lines
30 KiB
C
1292 lines
30 KiB
C
/* Grafx2 - The Ultimate 256-color bitmap paint program
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Copyright 2007 Adrien Destugues
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Copyright 1996-2001 Sunset Design (Guillaume Dorme & Karl Maritaud)
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Grafx2 is free software; you can redistribute it and/or
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modify it under the terms of the GNU General Public License
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as published by the Free Software Foundation; version 2
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of the License.
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Grafx2 is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with Grafx2; if not, see <http://www.gnu.org/licenses/>
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*/
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#include <assert.h>
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#include <unistd.h>
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#include <stdlib.h>
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#include <string.h>
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#include <stdio.h>
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#include <fcntl.h>
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#include <sys/stat.h>
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#include <math.h>
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#include "op_c.h"
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#include "errors.h"
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void RGB_to_HSL(int r,int g,int b,byte * hr,byte * sr,byte* lr)
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{
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double rd,gd,bd,h,s,l,max,min;
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// convert RGB to HSV
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rd = r / 255.0; // rd,gd,bd range 0-1 instead of 0-255
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gd = g / 255.0;
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bd = b / 255.0;
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// compute L
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// l=(rd*0.30)+(gd*0.59)+(bd*0.11);
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// compute maximum of rd,gd,bd
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if (rd>=gd)
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{
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if (rd>=bd)
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max = rd;
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else
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max = bd;
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}
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else
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{
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if (gd>=bd)
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max = gd;
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else
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max = bd;
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}
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// compute minimum of rd,gd,bd
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if (rd<=gd)
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{
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if (rd<=bd)
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min = rd;
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else
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min = bd;
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}
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else
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{
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if (gd<=bd)
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min = gd;
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else
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min = bd;
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}
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l = (max + min) / 2.0;
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if(max==min)
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s = h = 0;
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else
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{
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if (l<=0.5)
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s = (max - min) / (max + min);
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else
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s = (max - min) / (2 - (max + min));
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if (max == rd)
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h = 42.5 * (gd-bd)/(max-min);
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else if (max == gd)
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h = 42.5 * (bd-rd)/(max-min)+85;
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else
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h = 42.5 * (rd-gd)/(max-min)+170;
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if (h<0) h+=255;
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}
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*hr = h;
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*lr = (l*255.0);
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*sr = (s*255.0);
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}
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void HSL_to_RGB(byte h,byte s,byte l, byte* r, byte* g, byte* b)
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{
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float rf =0 ,gf = 0,bf = 0;
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float hf,lf,sf;
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float p,q;
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if(s==0)
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{
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*r=*g=*b=l;
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return;
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}
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hf = h / 255.0;
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lf = l / 255.0;
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sf = s / 255.0;
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if (lf<=0.5)
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q = lf*(1+sf);
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else
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q = lf+sf-lf*sf;
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p = 2*lf-q;
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rf = hf + (1 / 3.0);
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gf = hf;
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bf = hf - (1 / 3.0);
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if (rf < 0) rf+=1;
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if (rf > 1) rf-=1;
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if (gf < 0) gf+=1;
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if (gf > 1) gf-=1;
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if (bf < 0) bf+=1;
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if (bf > 1) bf-=1;
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if (rf < 1/6.0)
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rf = p + ((q-p)*6*rf);
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else if(rf < 0.5)
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rf = q;
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else if(rf < 2/3.0)
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rf = p + ((q-p)*6*(2/3.0-rf));
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else
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rf = p;
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if (gf < 1/6.0)
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gf = p + ((q-p)*6*gf);
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else if(gf < 0.5)
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gf = q;
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else if(gf < 2/3.0)
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gf = p + ((q-p)*6*(2/3.0-gf));
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else
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gf = p;
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if (bf < 1/6.0)
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bf = p + ((q-p)*6*bf);
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else if(bf < 0.5)
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bf = q;
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else if(bf < 2/3.0)
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bf = p + ((q-p)*6*(2/3.0-bf));
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else
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bf = p;
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*r = rf * (255);
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*g = gf * (255);
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*b = bf * (255);
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}
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/////////////////////////////////////////////////////////////////////////////
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///////////////////////////// Méthodes de gestion des tables de conversion //
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/////////////////////////////////////////////////////////////////////////////
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T_Conversion_table * CT_new(int nbb_r,int nbb_g,int nbb_b)
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{
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T_Conversion_table * n;
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int size;
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n=(T_Conversion_table *)malloc(sizeof(T_Conversion_table));
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if (n!=NULL)
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{
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// On recopie les paramŠtres demand‚s
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n->nbb_r=nbb_r;
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n->nbb_g=nbb_g;
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n->nbb_b=nbb_b;
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// On calcule les autres
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n->rng_r=(1<<nbb_r);
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n->rng_g=(1<<nbb_g);
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n->rng_b=(1<<nbb_b);
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n->dec_r=nbb_g+nbb_b;
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n->dec_g=nbb_b;
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n->dec_b=0;
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n->red_r=8-nbb_r;
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n->red_g=8-nbb_g;
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n->red_b=8-nbb_b;
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// On tente d'allouer la table
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size=(n->rng_r)*(n->rng_g)*(n->rng_b);
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n->table=(byte *)malloc(size);
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if (n->table!=NULL)
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// C'est bon!
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memset(n->table,0,size); // Inutile, mais plus propre
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else
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{
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// Table impossible … allouer
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free(n);
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n=NULL;
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}
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}
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return n;
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}
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void CT_delete(T_Conversion_table * t)
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{
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free(t->table);
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free(t);
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}
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byte CT_get(T_Conversion_table * t,int r,int g,int b)
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{
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int index;
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// On réduit le nombre de bits par couleur
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r=(r>>t->red_r);
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g=(g>>t->red_g);
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b=(b>>t->red_b);
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// On recherche la couleur la plus proche dans la table de conversion
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index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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return t->table[index];
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}
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void CT_set(T_Conversion_table * t,int r,int g,int b,byte i)
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{
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int index;
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index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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t->table[index]=i;
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}
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/////////////////////////////////////////////////////////////////////////////
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/////////////////////////////// M‚thodes de gestion des tables d'occurence //
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/////////////////////////////////////////////////////////////////////////////
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void OT_init(T_Occurrence_table * t)
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{
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int size;
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size=(t->rng_r)*(t->rng_g)*(t->rng_b)*sizeof(int);
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memset(t->table,0,size); // On initialise … 0
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}
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T_Occurrence_table * OT_new(int nbb_r,int nbb_g,int nbb_b)
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{
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T_Occurrence_table * n;
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int size;
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n=(T_Occurrence_table *)malloc(sizeof(T_Occurrence_table));
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if (n!=0)
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{
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// On recopie les paramŠtres demand‚s
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n->nbb_r=nbb_r;
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n->nbb_g=nbb_g;
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n->nbb_b=nbb_b;
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// On calcule les autres
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n->rng_r=(1<<nbb_r);
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n->rng_g=(1<<nbb_g);
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n->rng_b=(1<<nbb_b);
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n->dec_r=nbb_g+nbb_b;
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n->dec_g=nbb_b;
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n->dec_b=0;
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n->red_r=8-nbb_r;
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n->red_g=8-nbb_g;
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n->red_b=8-nbb_b;
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// On tente d'allouer la table
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size=(n->rng_r)*(n->rng_g)*(n->rng_b)*sizeof(int);
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n->table=(int *)malloc(size);
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if (n->table!=0)
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// C'est bon! On initialise … 0
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OT_init(n);
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else
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{
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// Table impossible … allouer
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free(n);
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n=0;
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}
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}
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return n;
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}
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void OT_delete(T_Occurrence_table * t)
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{
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free(t->table);
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free(t);
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}
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int OT_get(T_Occurrence_table * t,int r,int g,int b)
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{
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int index;
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index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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return t->table[index];
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}
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void OT_inc(T_Occurrence_table * t,int r,int g,int b)
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{
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int index;
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r=(r>>t->red_r);
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g=(g>>t->red_g);
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b=(b>>t->red_b);
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index=(r<<t->dec_r) | (g<<t->dec_g) | (b<<t->dec_b);
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t->table[index]++;
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}
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void OT_count_occurrences(T_Occurrence_table* t, T_Bitmap24B image, int size)
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{
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T_Bitmap24B ptr;
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int index;
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for (index = size, ptr = image; index > 0; index--, ptr++)
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OT_inc(t, ptr->R, ptr->G, ptr->B);
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}
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int OT_count_colors(T_Occurrence_table * t)
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{
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int val; // Valeur de retour
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int nb; // Nombre de couleurs … tester
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int i; // Compteur de couleurs test‚es
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val = 0;
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nb=(t->rng_r)*(t->rng_g)*(t->rng_b);
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for (i = 0; i < nb; i++)
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if (t->table[i]>0)
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val++;
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return val;
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}
|
||
|
||
|
||
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/////////////////////////////////////////////////////////////////////////////
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///////////////////////////////////////// M‚thodes de gestion des clusters //
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||
/////////////////////////////////////////////////////////////////////////////
|
||
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void Cluster_pack(T_Cluster * c,T_Occurrence_table * to)
|
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{
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||
int rmin,rmax,vmin,vmax,bmin,bmax;
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int r,g,b;
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||
|
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// On cherche les mins et les maxs de chaque composante sur la couverture
|
||
|
||
// int nbocc;
|
||
|
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// On prédécale tout pour éviter de faire trop de bazar en se forçant à utiliser OT_get, plus rapide
|
||
rmin=c->rmax <<16; rmax=c->rmin << 16;
|
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vmin=c->vmax << 8; vmax=c->vmin << 8;
|
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bmin=c->bmax; bmax=c->bmin;
|
||
c->occurences=0;
|
||
/*
|
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for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
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for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
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{
|
||
nbocc=to->table[r + g + b]; // OT_get
|
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if (nbocc)
|
||
{
|
||
if (r<rmin) rmin=r;
|
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else if (r>rmax) rmax=r;
|
||
if (g<vmin) vmin=g;
|
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else if (g>vmax) vmax=g;
|
||
if (b<bmin) bmin=b;
|
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else if (b>bmax) bmax=b;
|
||
c->occurences+=nbocc;
|
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}
|
||
}
|
||
*/
|
||
|
||
// On recherche le minimum et le maximum en parcourant le cluster selon chaque composante,
|
||
// ça évite des accès mémoires inutiles, de plus chaque boucle est plus petite que la
|
||
// précédente puisqu'on connait une borne supplémentaire
|
||
|
||
for(r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
rmin=r;
|
||
goto RMAX;
|
||
}
|
||
}
|
||
RMAX:
|
||
for(r=c->rmax<<16;r>=rmin;r-=1<<16)
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
rmax=r;
|
||
goto VMIN;
|
||
}
|
||
}
|
||
VMIN:
|
||
for(g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
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for(r=rmin;r<=rmax;r+=1<<16)
|
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for(b=c->bmin;b<=c->bmax;b++)
|
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{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
vmin=g;
|
||
goto VMAX;
|
||
}
|
||
}
|
||
VMAX:
|
||
for(g=c->vmax<<8;g>=vmin;g-=1<<8)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
vmax=g;
|
||
goto BMIN;
|
||
}
|
||
}
|
||
BMIN:
|
||
for(b=c->bmin;b<=c->bmax;b++)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
bmin=b;
|
||
goto BMAX;
|
||
}
|
||
}
|
||
BMAX:
|
||
for(b=c->bmax;b>=bmin;b--)
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
{
|
||
if(to->table[r + g + b]) // OT_get
|
||
{
|
||
bmax=b;
|
||
goto ENDCRUSH;
|
||
}
|
||
}
|
||
ENDCRUSH:
|
||
// Il faut quand même parcourir la partie utile du cluster, pour savoir combien il y a d'occurences
|
||
for(r=rmin;r<=rmax;r+=1<<16)
|
||
for(g=vmin;g<=vmax;g+=1<<8)
|
||
for(b=bmin;b<=bmax;b++)
|
||
{
|
||
c->occurences+=to->table[r + g + b]; // OT_get
|
||
}
|
||
|
||
c->rmin=rmin>>16; c->rmax=rmax>>16;
|
||
c->vmin=vmin>>8; c->vmax=vmax>>8;
|
||
c->bmin=bmin; c->bmax=bmax;
|
||
|
||
// On regarde la composante qui a la variation la plus grande
|
||
r=(c->rmax-c->rmin)*299;
|
||
g=(c->vmax-c->vmin)*587;
|
||
b=(c->bmax-c->bmin)*114;
|
||
|
||
if (g>=r)
|
||
{
|
||
// G>=R
|
||
if (g>=b)
|
||
{
|
||
// G>=R et G>=B
|
||
c->plus_large=1;
|
||
}
|
||
else
|
||
{
|
||
// G>=R et G<B
|
||
c->plus_large=2;
|
||
}
|
||
}
|
||
else
|
||
{
|
||
// R>G
|
||
if (r>=b)
|
||
{
|
||
// R>G et R>=B
|
||
c->plus_large=0;
|
||
}
|
||
else
|
||
{
|
||
// R>G et R<B
|
||
c->plus_large=2;
|
||
}
|
||
}
|
||
}
|
||
|
||
void Cluster_split(T_Cluster * c, T_Cluster * c1, T_Cluster * c2, int hue,
|
||
T_Occurrence_table * to)
|
||
{
|
||
int limit;
|
||
int cumul;
|
||
int r, g, b;
|
||
|
||
limit = c->occurences / 2;
|
||
cumul = 0;
|
||
if (hue == 0)
|
||
{
|
||
for (r = c->rmin<<16; r<=c->rmax<<16; r+=1<<16)
|
||
{
|
||
for (g = c->vmin<<8; g<=c->vmax<<8; g+=1<<8)
|
||
{
|
||
for (b = c->bmin; b<=c->bmax; b++)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16;
|
||
g>>=8;
|
||
|
||
if (r==c->rmin)
|
||
r++;
|
||
// R est la valeur de d‚but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=r-1;
|
||
c1->rmin=c->rmin; c1->rmax=r-1;
|
||
c1->Gmin=c->Gmin; c1->Vmax=c->Vmax;
|
||
c1->vmin=c->vmin; c1->vmax=c->vmax;
|
||
c1->Bmin=c->Bmin; c1->Bmax=c->Bmax;
|
||
c1->bmin=c->bmin; c1->bmax=c->bmax;
|
||
|
||
c2->Rmin=r; c2->Rmax=c->Rmax;
|
||
c2->rmin=r; c2->rmax=c->rmax;
|
||
c2->Gmin=c->Gmin; c2->Vmax=c->Vmax;
|
||
c2->vmin=c->vmin; c2->vmax=c->vmax;
|
||
c2->Bmin=c->Bmin; c2->Bmax=c->Bmax;
|
||
c2->bmin=c->bmin; c2->bmax=c->bmax;
|
||
}
|
||
else
|
||
if (hue==1)
|
||
{
|
||
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
{
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
{
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16; g>>=8;
|
||
|
||
if (g==c->vmin)
|
||
g++;
|
||
// G est la valeur de d‚but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=c->Rmax;
|
||
c1->rmin=c->rmin; c1->rmax=c->rmax;
|
||
c1->Gmin=c->Gmin; c1->Vmax=g-1;
|
||
c1->vmin=c->vmin; c1->vmax=g-1;
|
||
c1->Bmin=c->Bmin; c1->Bmax=c->Bmax;
|
||
c1->bmin=c->bmin; c1->bmax=c->bmax;
|
||
|
||
c2->Rmin=c->Rmin; c2->Rmax=c->Rmax;
|
||
c2->rmin=c->rmin; c2->rmax=c->rmax;
|
||
c2->Gmin=g; c2->Vmax=c->Vmax;
|
||
c2->vmin=g; c2->vmax=c->vmax;
|
||
c2->Bmin=c->Bmin; c2->Bmax=c->Bmax;
|
||
c2->bmin=c->bmin; c2->bmax=c->bmax;
|
||
}
|
||
else
|
||
{
|
||
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
for (g=c->vmin<<8;g<=c->vmax<<8;g+=1<<8)
|
||
{
|
||
for (r=c->rmin<<16;r<=c->rmax<<16;r+=1<<16)
|
||
{
|
||
cumul+=to->table[r + g + b];
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
if (cumul>=limit)
|
||
break;
|
||
}
|
||
|
||
r>>=16; g>>=8;
|
||
|
||
if (b==c->bmin)
|
||
b++;
|
||
// B est la valeur de d‚but du 2nd cluster
|
||
|
||
c1->Rmin=c->Rmin; c1->Rmax=c->Rmax;
|
||
c1->rmin=c->rmin; c1->rmax=c->rmax;
|
||
c1->Gmin=c->Gmin; c1->Vmax=c->Vmax;
|
||
c1->vmin=c->vmin; c1->vmax=c->vmax;
|
||
c1->Bmin=c->Bmin; c1->Bmax=b-1;
|
||
c1->bmin=c->bmin; c1->bmax=b-1;
|
||
|
||
c2->Rmin=c->Rmin; c2->Rmax=c->Rmax;
|
||
c2->rmin=c->rmin; c2->rmax=c->rmax;
|
||
c2->Gmin=c->Gmin; c2->Vmax=c->Vmax;
|
||
c2->vmin=c->vmin; c2->vmax=c->vmax;
|
||
c2->Bmin=b; c2->Bmax=c->Bmax;
|
||
c2->bmin=b; c2->bmax=c->bmax;
|
||
}
|
||
}
|
||
|
||
void Cluster_compute_hue(T_Cluster * c,T_Occurrence_table * to)
|
||
{
|
||
int cumul_r,cumul_g,cumul_b;
|
||
int r,g,b;
|
||
int nbocc;
|
||
|
||
byte s=0;
|
||
|
||
cumul_r=cumul_g=cumul_b=0;
|
||
for (r=c->rmin;r<=c->rmax;r++)
|
||
for (g=c->vmin;g<=c->vmax;g++)
|
||
for (b=c->bmin;b<=c->bmax;b++)
|
||
{
|
||
nbocc=OT_get(to,r,g,b);
|
||
if (nbocc)
|
||
{
|
||
cumul_r+=r*nbocc;
|
||
cumul_g+=g*nbocc;
|
||
cumul_b+=b*nbocc;
|
||
}
|
||
}
|
||
|
||
c->r=(cumul_r<<to->red_r)/c->occurences;
|
||
c->g=(cumul_g<<to->red_g)/c->occurences;
|
||
c->b=(cumul_b<<to->red_b)/c->occurences;
|
||
RGB_to_HSL(c->r, c->g, c->b, &c->h, &s, &c->l);
|
||
}
|
||
|
||
|
||
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
//////////////////////////// M‚thodes de gestion des ensembles de clusters //
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
|
||
// Debug helper : check if a cluster set has the right count value
|
||
/*
|
||
void CS_Check(T_Cluster_set* cs)
|
||
{
|
||
int i;
|
||
T_Cluster* c = cs->clusters;
|
||
for (i = cs->nb; i > 0; i--)
|
||
{
|
||
assert( c != NULL);
|
||
c = c->next;
|
||
}
|
||
|
||
assert(c == NULL);
|
||
}
|
||
*/
|
||
|
||
/// Setup the first cluster before we start the operations
|
||
void CS_Init(T_Cluster_set * cs, T_Occurrence_table * to)
|
||
{
|
||
cs->clusters->Rmin = cs->clusters->rmin = 0;
|
||
cs->clusters->Gmin = cs->clusters->vmin = 0;
|
||
cs->clusters->Bmin = cs->clusters->bmin = 0;
|
||
cs->clusters->Rmax = cs->clusters->rmax = to->rng_r - 1;
|
||
cs->clusters->Vmax = cs->clusters->vmax = to->rng_g - 1;
|
||
cs->clusters->Bmax = cs->clusters->bmax = to->rng_b - 1;
|
||
cs->clusters->next = NULL;
|
||
Cluster_pack(cs->clusters, to);
|
||
cs->nb = 1;
|
||
}
|
||
|
||
/// Allocate a new cluster set
|
||
T_Cluster_set * CS_New(int nbmax, T_Occurrence_table * to)
|
||
{
|
||
T_Cluster_set * n;
|
||
|
||
n=(T_Cluster_set *)malloc(sizeof(T_Cluster_set));
|
||
if (n != NULL)
|
||
{
|
||
// On recopie les paramŠtres demand‚s
|
||
n->nb_max = OT_count_colors(to);
|
||
|
||
// On vient de compter le nombre de couleurs existantes, s'il est plus grand
|
||
// que 256 on limite à 256
|
||
// (nombre de couleurs voulu au final)
|
||
if (n->nb_max > nbmax)
|
||
{
|
||
n->nb_max = nbmax;
|
||
}
|
||
|
||
// On tente d'allouer le premier cluster
|
||
n->clusters=(T_Cluster *)malloc(sizeof(T_Cluster));
|
||
if (n->clusters != NULL)
|
||
// C'est bon! On initialise
|
||
CS_Init(n, to);
|
||
else
|
||
{
|
||
// Table impossible … allouer
|
||
free(n);
|
||
n = NULL;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
/// Free a cluster set
|
||
void CS_Delete(T_Cluster_set * cs)
|
||
{
|
||
T_Cluster* nxt;
|
||
while (cs->clusters != NULL)
|
||
{
|
||
nxt = cs->clusters->next;
|
||
free(cs->clusters);
|
||
cs->clusters = nxt;
|
||
}
|
||
free(cs);
|
||
}
|
||
|
||
void CS_Get(T_Cluster_set * cs, T_Cluster * c)
|
||
{
|
||
T_Cluster* current = cs->clusters;
|
||
T_Cluster* prev = NULL;
|
||
|
||
// Search a cluster with at least 2 distinct colors so we can split it
|
||
do
|
||
{
|
||
if ( (current->rmin < current->rmax) ||
|
||
(current->vmin < current->vmax) ||
|
||
(current->bmin < current->bmax) )
|
||
break;
|
||
|
||
prev = current;
|
||
|
||
} while((current = current -> next));
|
||
|
||
// copy it to c
|
||
*c = *current;
|
||
|
||
// remove it from the list
|
||
cs->nb--;
|
||
|
||
if(prev)
|
||
prev->next = current->next;
|
||
else
|
||
cs->clusters = current->next;
|
||
free(current);
|
||
current = NULL;
|
||
}
|
||
|
||
void CS_Set(T_Cluster_set * cs,T_Cluster * c)
|
||
{
|
||
T_Cluster* current = cs->clusters;
|
||
T_Cluster* prev = NULL;
|
||
|
||
// Search the first cluster that is smaller than ours
|
||
while (current && current->occurences > c->occurences)
|
||
{
|
||
prev = current;
|
||
current = current->next;
|
||
}
|
||
|
||
// Now insert our cluster just before the one we found
|
||
c -> next = current;
|
||
|
||
current = malloc(sizeof(T_Cluster));
|
||
*current = *c ;
|
||
|
||
if (prev) prev->next = current;
|
||
else cs->clusters = current;
|
||
|
||
cs->nb++;
|
||
}
|
||
|
||
// Détermination de la meilleure palette en utilisant l'algo Median Cut :
|
||
// 1) On considère l'espace (R,G,B) comme 1 boîte
|
||
// 2) On cherche les extrêmes de la boîte en (R,G,B)
|
||
// 3) On trie les pixels de l'image selon l'axe le plus long parmi (R,G,B)
|
||
// 4) On coupe la boîte en deux au milieu, et on compacte pour que chaque bord
|
||
// corresponde bien à un pixel extreme
|
||
// 5) On recommence à couper selon le plus grand axe toutes boîtes confondues
|
||
// 6) On s'arrête quand on a le nombre de couleurs voulu
|
||
void CS_Generate(T_Cluster_set * cs, T_Occurrence_table * to)
|
||
{
|
||
T_Cluster current;
|
||
T_Cluster Nouveau1;
|
||
T_Cluster Nouveau2;
|
||
|
||
// Tant qu'on a moins de 256 clusters
|
||
while (cs->nb<cs->nb_max)
|
||
{
|
||
// On récupère le plus grand cluster
|
||
CS_Get(cs,¤t);
|
||
|
||
// On le coupe en deux
|
||
Cluster_split(¤t, &Nouveau1, &Nouveau2, current.plus_large, to);
|
||
|
||
// On compacte ces deux nouveaux (il peut y avoir un espace entre l'endroit
|
||
// de la coupure et les premiers pixels du cluster)
|
||
Cluster_pack(&Nouveau1, to);
|
||
Cluster_pack(&Nouveau2, to);
|
||
|
||
// On les remet dans le set
|
||
CS_Set(cs,&Nouveau1);
|
||
CS_Set(cs,&Nouveau2);
|
||
}
|
||
}
|
||
|
||
void CS_Compute_colors(T_Cluster_set * cs, T_Occurrence_table * to)
|
||
{
|
||
T_Cluster * c;
|
||
|
||
for (c=cs->clusters;c!=NULL;c=c->next)
|
||
Cluster_compute_hue(c,to);
|
||
}
|
||
|
||
void CS_Sort_by_chrominance(T_Cluster_set * cs)
|
||
{
|
||
T_Cluster* nc;
|
||
T_Cluster* prev = NULL;
|
||
T_Cluster* place;
|
||
T_Cluster* newlist = NULL;
|
||
|
||
while (cs->clusters)
|
||
{
|
||
// Remove the first cluster from the original list
|
||
nc = cs->clusters;
|
||
cs->clusters = cs->clusters->next;
|
||
|
||
// Find his position in the new list
|
||
for (place = newlist; place != NULL; place = place->next)
|
||
{
|
||
if (place->h > nc->h) break;
|
||
prev = place;
|
||
}
|
||
|
||
// Chain it there
|
||
nc->next = place;
|
||
if (prev) prev->next = nc;
|
||
else newlist = nc;
|
||
|
||
prev = NULL;
|
||
}
|
||
|
||
// Put the new list bavk in place
|
||
cs->clusters = newlist;
|
||
}
|
||
|
||
void CS_Sort_by_luminance(T_Cluster_set * cs)
|
||
{
|
||
T_Cluster* nc;
|
||
T_Cluster* prev = NULL;
|
||
T_Cluster* place;
|
||
T_Cluster* newlist = NULL;
|
||
|
||
while (cs->clusters)
|
||
{
|
||
// Remove the first cluster from the original list
|
||
nc = cs->clusters;
|
||
cs->clusters = cs->clusters->next;
|
||
|
||
// Find its position in the new list
|
||
for (place = newlist; place != NULL; place = place->next)
|
||
{
|
||
if (place->l > nc->l) break;
|
||
prev = place;
|
||
}
|
||
|
||
// Chain it there
|
||
nc->next = place;
|
||
if (prev) prev->next = nc;
|
||
else newlist = nc;
|
||
|
||
// reset prev pointer
|
||
prev = NULL;
|
||
}
|
||
|
||
// Put the new list back in place
|
||
cs->clusters = newlist;
|
||
}
|
||
|
||
void CS_Generate_color_table_and_palette(T_Cluster_set * cs,T_Conversion_table * tc,T_Components * palette)
|
||
{
|
||
int index;
|
||
int r,g,b;
|
||
T_Cluster* current = cs->clusters;
|
||
|
||
for (index=0;index<cs->nb;index++)
|
||
{
|
||
palette[index].R=current->r;
|
||
palette[index].G=current->g;
|
||
palette[index].B=current->b;
|
||
|
||
for (r=current->Rmin; r<=current->Rmax; r++)
|
||
for (g=current->Gmin;g<=current->Vmax;g++)
|
||
for (b=current->Bmin;b<=current->Bmax;b++)
|
||
CT_set(tc,r,g,b,index);
|
||
current = current->next;
|
||
}
|
||
}
|
||
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
///////////////////////////////////////// Méthodes de gestion des dégradés //
|
||
/////////////////////////////////////////////////////////////////////////////
|
||
|
||
void GS_Init(T_Gradient_set * ds,T_Cluster_set * cs)
|
||
{
|
||
ds->gradients[0].nb_colors=1;
|
||
ds->gradients[0].min=cs->clusters->h;
|
||
ds->gradients[0].max=cs->clusters->h;
|
||
ds->gradients[0].hue=cs->clusters->h;
|
||
// Et hop : le 1er ensemble de d‚grad‚s est initialis‚
|
||
ds->nb=1;
|
||
}
|
||
|
||
T_Gradient_set * GS_New(T_Cluster_set * cs)
|
||
{
|
||
T_Gradient_set * n;
|
||
|
||
n=(T_Gradient_set *)malloc(sizeof(T_Gradient_set));
|
||
if (n!=NULL)
|
||
{
|
||
// On recopie les paramŠtres demand‚s
|
||
n->nb_max=cs->nb_max;
|
||
|
||
// On tente d'allouer la table
|
||
n->gradients=(T_Gradient *)malloc((n->nb_max)*sizeof(T_Gradient));
|
||
if (n->gradients!=0)
|
||
// C'est bon! On initialise
|
||
GS_Init(n,cs);
|
||
else
|
||
{
|
||
// Table impossible … allouer
|
||
free(n);
|
||
n=0;
|
||
}
|
||
}
|
||
|
||
return n;
|
||
}
|
||
|
||
void GS_Delete(T_Gradient_set * ds)
|
||
{
|
||
free(ds->gradients);
|
||
free(ds);
|
||
}
|
||
|
||
void GS_Generate(T_Gradient_set * ds,T_Cluster_set * cs)
|
||
{
|
||
int id; // Les indexs de parcours des ensembles
|
||
int best_gradient; // Meilleur d‚grad‚
|
||
int best_diff; // Meilleure diff‚rence de chrominance
|
||
int diff; // difference de chrominance courante
|
||
T_Cluster * current = cs->clusters;
|
||
|
||
// Pour chacun des clusters … traiter
|
||
do
|
||
{
|
||
// On recherche le d‚grad‚ le plus proche de la chrominance du cluster
|
||
best_gradient=-1;
|
||
best_diff=99999999;
|
||
for (id=0;id<ds->nb;id++)
|
||
{
|
||
diff=abs(current->h - ds->gradients[id].hue);
|
||
if ((best_diff>diff) && (diff<16))
|
||
{
|
||
best_gradient=id;
|
||
best_diff=diff;
|
||
}
|
||
}
|
||
|
||
// Si on a trouv‚ un d‚grad‚ dans lequel inclure le cluster
|
||
if (best_gradient!=-1)
|
||
{
|
||
// On met … jour le d‚grad‚
|
||
if (current->h < ds->gradients[best_gradient].min)
|
||
ds->gradients[best_gradient].min=current->h;
|
||
if (current->h > ds->gradients[best_gradient].max)
|
||
ds->gradients[best_gradient].max=current->h;
|
||
ds->gradients[best_gradient].hue=((ds->gradients[best_gradient].hue*
|
||
ds->gradients[best_gradient].nb_colors)
|
||
+current->h)
|
||
/(ds->gradients[best_gradient].nb_colors+1);
|
||
ds->gradients[best_gradient].nb_colors++;
|
||
}
|
||
else
|
||
{
|
||
// On cr‚e un nouveau d‚grad‚
|
||
best_gradient=ds->nb;
|
||
ds->gradients[best_gradient].nb_colors=1;
|
||
ds->gradients[best_gradient].min=current->h;
|
||
ds->gradients[best_gradient].max=current->h;
|
||
ds->gradients[best_gradient].hue=current->h;
|
||
ds->nb++;
|
||
}
|
||
current->h=best_gradient;
|
||
} while((current = current->next));
|
||
|
||
// On redistribue les valeurs dans les clusters
|
||
current = cs -> clusters;
|
||
do
|
||
current->h=ds->gradients[current->h].hue;
|
||
while((current = current ->next));
|
||
}
|
||
|
||
|
||
|
||
|
||
T_Conversion_table * Optimize_palette(T_Bitmap24B image, int size,
|
||
T_Components * palette, int r, int g, int b)
|
||
{
|
||
T_Occurrence_table * to;
|
||
T_Conversion_table * tc;
|
||
T_Cluster_set * cs;
|
||
T_Gradient_set * ds;
|
||
|
||
// Création des éléments nécessaires au calcul de palette optimisée:
|
||
to = 0; tc = 0; cs = 0; ds = 0;
|
||
|
||
to = OT_new(r, g, b);
|
||
if (to == NULL)
|
||
return 0;
|
||
|
||
tc = CT_new(r, g, b);
|
||
if (tc == NULL)
|
||
{
|
||
OT_delete(to);
|
||
return 0;
|
||
}
|
||
|
||
// Première étape : on compte les pixels de chaque couleur pour pouvoir trier là dessus
|
||
OT_count_occurrences(to, image, size);
|
||
|
||
cs = CS_New(256, to);
|
||
if (cs == NULL)
|
||
{
|
||
CT_delete(tc);
|
||
OT_delete(to);
|
||
return 0;
|
||
}
|
||
//CS_Check(cs);
|
||
// C'est bon, on a pu tout allouer
|
||
|
||
// On génère les clusters (avec l'algo du median cut)
|
||
CS_Generate(cs, to);
|
||
//CS_Check(cs);
|
||
|
||
// On calcule la teinte de chaque pixel (Luminance et chrominance)
|
||
CS_Compute_colors(cs, to);
|
||
//CS_Check(cs);
|
||
|
||
ds = GS_New(cs);
|
||
if (ds!= NULL)
|
||
{
|
||
GS_Generate(ds, cs);
|
||
GS_Delete(ds);
|
||
}
|
||
// Enfin on trie les clusters (donc les couleurs de la palette) dans un ordre
|
||
// sympa : par couleur, et par luminosité pour chaque couleur
|
||
CS_Sort_by_luminance(cs);
|
||
//CS_Check(cs);
|
||
CS_Sort_by_chrominance(cs);
|
||
//CS_Check(cs);
|
||
|
||
// Enfin on génère la palette et la table de correspondance entre chaque
|
||
// couleur 24b et sa couleur palette associée.
|
||
CS_Generate_color_table_and_palette(cs, tc, palette);
|
||
//CS_Check(cs);
|
||
|
||
CS_Delete(cs);
|
||
OT_delete(to);
|
||
return tc;
|
||
}
|
||
|
||
int Modified_value(int value,int modif)
|
||
{
|
||
value+=modif;
|
||
if (value<0)
|
||
{
|
||
value=0;
|
||
}
|
||
else if (value>255)
|
||
{
|
||
value=255;
|
||
}
|
||
return value;
|
||
}
|
||
|
||
void Convert_24b_bitmap_to_256_Floyd_Steinberg(T_Bitmap256 dest,T_Bitmap24B source,int width,int height,T_Components * palette,T_Conversion_table * tc)
|
||
// Cette fonction dégrade au fur et à mesure le bitmap source, donc soit on ne
|
||
// s'en ressert pas, soit on passe à la fonction une copie de travail du
|
||
// bitmap original.
|
||
{
|
||
T_Bitmap24B current;
|
||
T_Bitmap24B c_plus1;
|
||
T_Bitmap24B u_minus1;
|
||
T_Bitmap24B next;
|
||
T_Bitmap24B u_plus1;
|
||
T_Bitmap256 d;
|
||
int x_pos,y_pos;
|
||
int red,green,blue;
|
||
float e_red,e_green,e_blue;
|
||
|
||
// On initialise les variables de parcours:
|
||
current =source; // Le pixel dont on s'occupe
|
||
next =current+width; // Le pixel en dessous
|
||
c_plus1 =current+1; // Le pixel à droite
|
||
u_minus1=next-1; // Le pixel en bas à gauche
|
||
u_plus1 =next+1; // Le pixel en bas à droite
|
||
d =dest;
|
||
|
||
// On parcours chaque pixel:
|
||
for (y_pos=0;y_pos<height;y_pos++)
|
||
{
|
||
for (x_pos=0;x_pos<width;x_pos++)
|
||
{
|
||
// On prends la meilleure couleur de la palette qui traduit la couleur
|
||
// 24 bits de la source:
|
||
red=current->R;
|
||
green =current->G;
|
||
blue =current->B;
|
||
// Cherche la couleur correspondant dans la palette et la range dans l'image de destination
|
||
*d=CT_get(tc,red,green,blue);
|
||
|
||
// Puis on calcule pour chaque composante l'erreur dûe à l'approximation
|
||
red-=palette[*d].R;
|
||
green -=palette[*d].G;
|
||
blue -=palette[*d].B;
|
||
|
||
// Et dans chaque pixel voisin on propage l'erreur
|
||
// A droite:
|
||
e_red=(red*7)/16.0;
|
||
e_green =(green *7)/16.0;
|
||
e_blue =(blue *7)/16.0;
|
||
if (x_pos+1<width)
|
||
{
|
||
// Modified_value fait la somme des 2 params en bornant sur [0,255]
|
||
c_plus1->R=Modified_value(c_plus1->R,e_red);
|
||
c_plus1->G=Modified_value(c_plus1->G,e_green );
|
||
c_plus1->B=Modified_value(c_plus1->B,e_blue );
|
||
}
|
||
// En bas à gauche:
|
||
if (y_pos+1<height)
|
||
{
|
||
e_red=(red*3)/16.0;
|
||
e_green =(green *3)/16.0;
|
||
e_blue =(blue *3)/16.0;
|
||
if (x_pos>0)
|
||
{
|
||
u_minus1->R=Modified_value(u_minus1->R,e_red);
|
||
u_minus1->G=Modified_value(u_minus1->G,e_green );
|
||
u_minus1->B=Modified_value(u_minus1->B,e_blue );
|
||
}
|
||
// En bas:
|
||
e_red=(red*5/16.0);
|
||
e_green =(green*5 /16.0);
|
||
e_blue =(blue*5 /16.0);
|
||
next->R=Modified_value(next->R,e_red);
|
||
next->G=Modified_value(next->G,e_green );
|
||
next->B=Modified_value(next->B,e_blue );
|
||
// En bas à droite:
|
||
if (x_pos+1<width)
|
||
{
|
||
e_red=(red/16.0);
|
||
e_green =(green /16.0);
|
||
e_blue =(blue /16.0);
|
||
u_plus1->R=Modified_value(u_plus1->R,e_red);
|
||
u_plus1->G=Modified_value(u_plus1->G,e_green );
|
||
u_plus1->B=Modified_value(u_plus1->B,e_blue );
|
||
}
|
||
}
|
||
|
||
// On passe au pixel suivant :
|
||
current++;
|
||
c_plus1++;
|
||
u_minus1++;
|
||
next++;
|
||
u_plus1++;
|
||
d++;
|
||
}
|
||
}
|
||
}
|
||
|
||
void Convert_24b_bitmap_to_256_nearest_neighbor(T_Bitmap256 dest,
|
||
T_Bitmap24B source, int width, int height, T_Components * palette,
|
||
T_Conversion_table * tc)
|
||
{
|
||
T_Bitmap24B current;
|
||
T_Bitmap256 d;
|
||
int x_pos, y_pos;
|
||
int red, green, blue;
|
||
|
||
// On initialise les variables de parcours:
|
||
current =source; // Le pixel dont on s'occupe
|
||
|
||
d =dest;
|
||
|
||
// On parcours chaque pixel:
|
||
for (y_pos = 0; y_pos < height; y_pos++)
|
||
{
|
||
for (x_pos = 0 ;x_pos < width; x_pos++)
|
||
{
|
||
// On prends la meilleure couleur de la palette qui traduit la couleur
|
||
// 24 bits de la source:
|
||
red = current->R;
|
||
green = current->G;
|
||
blue = current->B;
|
||
// Cherche la couleur correspondant dans la palette et la range dans
|
||
// l'image de destination
|
||
*d = CT_get(tc, red, green, blue);
|
||
|
||
// On passe au pixel suivant :
|
||
current++;
|
||
d++;
|
||
}
|
||
}
|
||
}
|
||
|
||
|
||
static const byte precision_24b[]=
|
||
{
|
||
8,8,8,
|
||
6,6,6,
|
||
6,6,5,
|
||
5,6,5,
|
||
5,5,5,
|
||
5,5,4,
|
||
4,5,4,
|
||
4,4,4,
|
||
4,4,3,
|
||
3,4,3,
|
||
3,3,3,
|
||
3,3,2};
|
||
|
||
|
||
// Convertie avec le plus de précision possible une image 24b en 256c
|
||
// Renvoie s'il y a eu une erreur ou pas..
|
||
|
||
// Cette fonction utilise l'algorithme "median cut" (Optimize_palette) pour trouver la palette, et diffuse les erreurs avec floyd-steinberg.
|
||
|
||
int Convert_24b_bitmap_to_256(T_Bitmap256 dest,T_Bitmap24B source,int width,int height,T_Components * palette)
|
||
{
|
||
T_Conversion_table * table; // table de conversion
|
||
int ip; // index de précision pour la conversion
|
||
|
||
// On essaye d'obtenir une table de conversion qui loge en mémoire, avec la
|
||
// meilleure précision possible
|
||
for (ip=0;ip<(10*3);ip+=3)
|
||
{
|
||
table=Optimize_palette(source,width*height,palette,precision_24b[ip+0],
|
||
precision_24b[ip+1],precision_24b[ip+2]);
|
||
if (table!=0)
|
||
break;
|
||
}
|
||
|
||
if (table!=0)
|
||
{
|
||
//Convert_24b_bitmap_to_256_Floyd_Steinberg(dest,source,width,height,palette,table);
|
||
Convert_24b_bitmap_to_256_nearest_neighbor(dest,source,width,height,palette,table);
|
||
CT_delete(table);
|
||
return 0;
|
||
}
|
||
else
|
||
return 1;
|
||
}
|
||
|
||
|
||
|