/*
 *
 *  This file is part of the XForms library package.
 *
 * XForms is free software; you can redistribute it and/or modify it
 * under the terms of the GNU Lesser General Public License as
 * published by the Free Software Foundation; either version 2.1, or
 * (at your option) any later version.
 *
 * XForms 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
 * Lesser General Public License for more details.
 *
 * You should have received a copy of the GNU Lesser General Public
 * License along with XForms; see the file COPYING.  If not, write to
 * the Free Software Foundation, 59 Temple Place - Suite 330, Boston,
 * MA 02111-1307, USA.
 *
 */


/*
 * $Id: image_jquant.c,v 1.0 2002/05/08 05:16:30 zhao Release $
 *
 * Copyright (C) 1998  T.C. Zhao
 *
 * The 2-pass quantizer from the JPEG distribution by the
 * Independent JPEG group. Except for minor interface changes, the code
 * here is almost verbatim copy of the IJG's code, which
 * has the following copyright:
 *
 * Copyright (C) 1991-1996, Thomas G. Lane.
 *  This file is part of the XForms library package.
 *
 */

#include "forms.h"
#include "flimage.h"
#include "flimage_int.h"

void
fl_select_mediancut_quantizer(void)
{
    flimage_quantize_rgb = fl_j2pass_quantize_rgb;
    flimage_quantize_packed = fl_j2pass_quantize_packed;
}


#define R_SCALE 2		/* scale R distances by this much */
#define G_SCALE 3		/* scale G distances by this much */
#define B_SCALE 1		/* and B by this much */

#define C0_SCALE  R_SCALE
#define C1_SCALE  G_SCALE
#define C2_SCALE  B_SCALE

#define LOCAL(a)           static a
#define METHODDEF(a)       static a

#define BITS_IN_JSAMPLE   FL_PCBITS
#define MAXJSAMPLE   ((1<<BITS_IN_JSAMPLE)-1)

typedef unsigned char JSAMPLE;
#define GETJSAMPLE(a)        ((a)&0xff)

#define MAXNUMCOLORS  (MAXJSAMPLE+1)	/* maximum size of colormap */

/* These will do the right thing for either R,G,B or B,G,R color order,
 * but you may not like the results for other color orders.
 */
#define HIST_C0_BITS  5		/* bits of precision in R/B histogram */
#define HIST_C1_BITS  6		/* bits of precision in G histogram */
#define HIST_C2_BITS  5		/* bits of precision in B/R histogram */

/* Number of elements along histogram axes. */
#define HIST_C0_ELEMS  (1<<HIST_C0_BITS)
#define HIST_C1_ELEMS  (1<<HIST_C1_BITS)
#define HIST_C2_ELEMS  (1<<HIST_C2_BITS)

/* These are the amounts to shift an input value to get a histogram index. */
#define C0_SHIFT  (BITS_IN_JSAMPLE-HIST_C0_BITS)
#define C1_SHIFT  (BITS_IN_JSAMPLE-HIST_C1_BITS)
#define C2_SHIFT  (BITS_IN_JSAMPLE-HIST_C2_BITS)

typedef u_short histcell;	/* histogram cell; prefer an unsigned type */
typedef histcell *histptr;	/* for pointers to histogram cells */
typedef histcell hist1d[HIST_C2_ELEMS];		/* typedefs for the array */
typedef hist1d *hist2d;		/* type for the 2nd-level pointers */
typedef hist2d *hist3d;		/* type for top-level pointer */

#if BITS_IN_JSAMPLE == 8
typedef short FSERROR;		/* 16 bits should be enough */
typedef int LOCFSERROR;		/* use 'int' for calculation temps */
#else
typedef int FSERROR;		/* may need more than 16 bits */
typedef int LOCFSERROR;		/* be sure calculation temps are big enough */
#endif

typedef FSERROR *FSERRPTR;	/* pointer to error array (in FAR storage!) */


typedef struct
{
    int c0min, c0max;
    int c1min, c1max;
    int c2min, c2max;
    int volume;
    long colorcount;
}
box;

typedef box *boxptr;


typedef struct
{
    hist3d histogram;		/* pointer to the 3D histogram array */
    FSERRPTR fserrors;		/* accumulated-errors array */
    int *error_limiter;		/* table for clamping the applied error */
    int on_odd_row;		/* flag to remember which row we are on */
    int *colormap[3];		/* selected colormap */
    int actual_number_of_colors;	/* number of selected colors */
    FL_IMAGE *im;		/* for progress monitor only          */
}
SPEC;


static void init_error_limit(SPEC *);
static void prescan_quantize(SPEC *, unsigned char **, unsigned char **,
			     unsigned char **, int, int);


static void select_colors(SPEC *sp, int desired_colors);
static void pass2_fs_dither(SPEC *, unsigned char **,
			    unsigned char **, unsigned char **,
			    unsigned short **, int, int);

static void
cleanup_spec(SPEC *sp)

{
    int i;

    if (sp->fserrors)
	fl_free(sp->fserrors);

    if (sp->error_limiter)
	fl_free(sp->error_limiter - MAXJSAMPLE);

    sp->error_limiter = 0;
    sp->fserrors = 0;

    if (sp->histogram)
    {
	for (i = 0; i < HIST_C0_ELEMS; i++)
	{
	    if (sp->histogram[i])
		fl_free(sp->histogram[i]);
	    sp->histogram[i] = 0;
	}
    }

    fl_free(sp->histogram);
    sp->histogram = 0;

    fl_free(sp);
}

static SPEC *
alloc_spec(int w, int h, int *rlut, int *glut, int *blut)
{
    int fs_size = (w + 2) * (3 * sizeof(FSERROR)), i;
    SPEC *sp = fl_calloc(1, sizeof(*sp));
    int err = !sp;

    if (!err)
	init_error_limit(sp);

    err = err || !(sp->fserrors = fl_calloc(1, fs_size));
    err = err || !(sp->histogram = fl_calloc(1, HIST_C0_ELEMS * sizeof(hist2d)));
    for (i = 0; !err && i < HIST_C0_ELEMS; i++)
	err = !(sp->histogram[i] = fl_calloc(1,
			 HIST_C1_ELEMS * HIST_C2_ELEMS * sizeof(histcell)));

    if (err)
    {
	cleanup_spec(sp);
	sp = 0;
    }
    else
    {
	sp->colormap[0] = rlut;
	sp->colormap[1] = glut;
	sp->colormap[2] = blut;
    }
    return sp;
}


int
fl_j2pass_quantize_rgb(unsigned char **red,
		       unsigned char **green,
		       unsigned char **blue, int w, int h,
		       int max_color,
		       unsigned short **ci, int *actual_color,
		       int *red_lut,
		       int *green_lut,
		       int *blue_lut, FL_IMAGE * im)
{
    SPEC *sp = alloc_spec(w, h, red_lut, green_lut, blue_lut);
    int i;

    if (!sp)
    {
	*actual_color = 0;
	if (im)
	    im->error_message(im, "Failed to allocate working memory");
	return -1;
    }

    if (*actual_color > 256)
	*actual_color = 256;

    sp->im = im;

    /* get histogram  */
    prescan_quantize(sp, red, green, blue, w, h);

    select_colors(sp, max_color);

    /* re-init histogram for inverse lookup */
    for (i = 0; i < HIST_C0_ELEMS; i++)
	memset(sp->histogram[i], 0,
	       HIST_C1_ELEMS * HIST_C2_ELEMS * sizeof(histcell));

    sp->on_odd_row = 0;
    pass2_fs_dither(sp, red, green, blue, ci, w, h);
    *actual_color = sp->actual_number_of_colors;
    cleanup_spec(sp);

    if (im)
    {
	im->completed = im->h;
	im->visual_cue(im, "Quantization Done");
    }

    return 0;
}

int
fl_j2pass_quantize_packed(unsigned int **packed,
			  int w, int h, int max_color,
			  unsigned short **ci, int *actual_color,
			  int *red_lut,
			  int *green_lut,
			  int *blue_lut, FL_IMAGE * im)
{

    SPEC *sp = alloc_spec(w, h, red_lut, green_lut, blue_lut);
    unsigned char **red = 0, **green = 0, **blue = 0;
    int i, err;

    if (!sp)
    {
	if (im)
	    im->error_message(im, "Quantize: can't allocate memory");
	*actual_color = 0;
	return -1;
    }

    sp->im = im;

    /* we can process the image one piece a time to avoid the heavy memory
       usage, but packed is not that common. For now, do it in one chunk */

    err = !(red = fl_get_matrix(h, w, sizeof(**red)));
    err = err || !(green = fl_get_matrix(h, w, sizeof(**red)));
    err = err || !(blue = fl_get_matrix(h, w, sizeof(**red)));

    if (err)
    {
	const char *s = "Quantize: can't allocate memory";
	if (im)
	    im->error_message(im, s);
	else
	    fprintf(stderr, "%s\n", s);

	fl_free_matrix(red);
	fl_free_matrix(green);
	fl_free_matrix(blue);
    }

    for (i = w * h; --i >= 0;)
	FL_UNPACK(packed[0][i], red[0][i], green[0][i], blue[0][i]);


    /* get histogram  */
    prescan_quantize(sp, red, green, blue, w, h);

    select_colors(sp, max_color);

    /* re-init histogram for inverse lookup */
    for (i = 0; i < HIST_C0_ELEMS; i++)
	memset(sp->histogram[i], 0,
	       HIST_C1_ELEMS * HIST_C2_ELEMS * sizeof(histcell));

    sp->on_odd_row = 0;
    pass2_fs_dither(sp, red, green, blue, ci, w, h);
    *actual_color = sp->actual_number_of_colors;

    fl_free_matrix(red);
    fl_free_matrix(green);
    fl_free_matrix(blue);
    cleanup_spec(sp);

    if (im)
    {
	im->completed = im->h;
	im->visual_cue(im, "Quantization Done");
    }

    return 0;
}


/* log2(histogram cells in update box) for each axis; this can be adjusted */
#define BOX_C0_LOG  (HIST_C0_BITS-3)
#define BOX_C1_LOG  (HIST_C1_BITS-3)
#define BOX_C2_LOG  (HIST_C2_BITS-3)

#define BOX_C0_ELEMS  (1<<BOX_C0_LOG)	/* # of hist cells in update box */
#define BOX_C1_ELEMS  (1<<BOX_C1_LOG)
#define BOX_C2_ELEMS  (1<<BOX_C2_LOG)

#define BOX_C0_SHIFT  (C0_SHIFT + BOX_C0_LOG)
#define BOX_C1_SHIFT  (C1_SHIFT + BOX_C1_LOG)
#define BOX_C2_SHIFT  (C2_SHIFT + BOX_C2_LOG)


LOCAL(int)
find_nearby_colors(SPEC *sp, int minc0, int minc1, int minc2,
		   JSAMPLE colorlist[])
/* Locate the colormap entries close enough to an update box to be candidates
 * for the nearest entry to some cell(s) in the update box.  The update box
 * is specified by the center coordinates of its first cell.  The number of
 * candidate colormap entries is returned, and their colormap indexes are
 * placed in colorlist[].
 * This routine uses Heckbert's "locally sorted search" criterion to select
 * the colors that need further consideration.
 */
{
    int numcolors = sp->actual_number_of_colors;
    int maxc0, maxc1, maxc2;
    int centerc0, centerc1, centerc2;
    int i, x, ncolors;
    int minmaxdist, min_dist, max_dist, tdist;
    int mindist[MAXNUMCOLORS];	/* min distance to colormap entry i */

    /* Compute true coordinates of update box's upper corner and center. *
       Actually we compute the coordinates of the center of the upper-corner
       * histogram cell, which are the upper bounds of the volume we care
       about. * Note that since ">>" rounds down, the "center" values may be
       closer to * min than to max; hence comparisons to them must be "<=",
       not "<". */
    maxc0 = minc0 + ((1 << BOX_C0_SHIFT) - (1 << C0_SHIFT));
    centerc0 = (minc0 + maxc0) >> 1;
    maxc1 = minc1 + ((1 << BOX_C1_SHIFT) - (1 << C1_SHIFT));
    centerc1 = (minc1 + maxc1) >> 1;
    maxc2 = minc2 + ((1 << BOX_C2_SHIFT) - (1 << C2_SHIFT));
    centerc2 = (minc2 + maxc2) >> 1;

    /* For each color in colormap, find: *  1. its minimum squared-distance
       to any point in the update box *     (zero if color is within update
       box); *  2. its maximum squared-distance to any point in the update
       box. * Both of these can be found by considering only the corners of
       the box. * We save the minimum distance for each color in mindist[]; * 








       only the smallest maximum distance is of interest. */
    minmaxdist = 0x7FFFFFFFL;

    for (i = 0; i < numcolors; i++)
    {
	/* We compute the squared-c0-distance term, then add in the other
	   two. */
	x = sp->colormap[0][i];
	if (x < minc0)
	{
	    tdist = (x - minc0) * C0_SCALE;
	    min_dist = tdist * tdist;
	    tdist = (x - maxc0) * C0_SCALE;
	    max_dist = tdist * tdist;
	}
	else if (x > maxc0)
	{
	    tdist = (x - maxc0) * C0_SCALE;
	    min_dist = tdist * tdist;
	    tdist = (x - minc0) * C0_SCALE;
	    max_dist = tdist * tdist;
	}
	else
	{
	    /* within cell range so no contribution to min_dist */
	    min_dist = 0;
	    if (x <= centerc0)
	    {
		tdist = (x - maxc0) * C0_SCALE;
		max_dist = tdist * tdist;
	    }
	    else
	    {
		tdist = (x - minc0) * C0_SCALE;
		max_dist = tdist * tdist;
	    }
	}

	x = sp->colormap[1][i];
	if (x < minc1)
	{
	    tdist = (x - minc1) * C1_SCALE;
	    min_dist += tdist * tdist;
	    tdist = (x - maxc1) * C1_SCALE;
	    max_dist += tdist * tdist;
	}
	else if (x > maxc1)
	{
	    tdist = (x - maxc1) * C1_SCALE;
	    min_dist += tdist * tdist;
	    tdist = (x - minc1) * C1_SCALE;
	    max_dist += tdist * tdist;
	}
	else
	{
	    /* within cell range so no contribution to min_dist */
	    if (x <= centerc1)
	    {
		tdist = (x - maxc1) * C1_SCALE;
		max_dist += tdist * tdist;
	    }
	    else
	    {
		tdist = (x - minc1) * C1_SCALE;
		max_dist += tdist * tdist;
	    }
	}

	x = sp->colormap[2][i];
	if (x < minc2)
	{
	    tdist = (x - minc2) * C2_SCALE;
	    min_dist += tdist * tdist;
	    tdist = (x - maxc2) * C2_SCALE;
	    max_dist += tdist * tdist;
	}
	else if (x > maxc2)
	{
	    tdist = (x - maxc2) * C2_SCALE;
	    min_dist += tdist * tdist;
	    tdist = (x - minc2) * C2_SCALE;
	    max_dist += tdist * tdist;
	}
	else
	{
	    /* within cell range so no contribution to min_dist */
	    if (x <= centerc2)
	    {
		tdist = (x - maxc2) * C2_SCALE;
		max_dist += tdist * tdist;
	    }
	    else
	    {
		tdist = (x - minc2) * C2_SCALE;
		max_dist += tdist * tdist;
	    }
	}

	mindist[i] = min_dist;	/* save away the results */
	if (max_dist < minmaxdist)
	    minmaxdist = max_dist;
    }

    /* Now we know that no cell in the update box is more than minmaxdist *
       away from some colormap entry.  Therefore, only colors that are *
       within minmaxdist of some part of the box need be considered. */
    ncolors = 0;
    for (i = 0; i < numcolors; i++)
    {
	if (mindist[i] <= minmaxdist)
	    colorlist[ncolors++] = (JSAMPLE) i;
    }
    return ncolors;
}


LOCAL(void)
find_best_colors(SPEC *sp, int minc0, int minc1, int minc2,
		 int numcolors, JSAMPLE colorlist[], JSAMPLE bestcolor[])
/* Find the closest colormap entry for each cell in the update box,
 * given the list of candidate colors prepared by find_nearby_colors.
 * Return the indexes of the closest entries in the bestcolor[] array.
 * This routine uses Thomas' incremental distance calculation method to
 * find the distance from a colormap entry to successive cells in the box.
 */
{
    int ic0, ic1, ic2;
    int i, icolor;
    register int *bptr;		/* pointer into bestdist[] array */
    JSAMPLE *cptr;		/* pointer into bestcolor[] array */
    int dist0, dist1;		/* initial distance values */
    register int dist2;		/* current distance in inner loop */
    int xx0, xx1;		/* distance increments */
    register int xx2;
    int inc0, inc1, inc2;	/* initial values for increments */
    /* This array holds the distance to the nearest-so-far color for each
       cell */
    int bestdist[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];

    /* Initialize best-distance for each cell of the update box */
    bptr = bestdist;
    for (i = BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS - 1; i >= 0; i--)
	*bptr++ = 0x7FFFFFFFL;

    /* For each color selected by find_nearby_colors, * compute its distance
       to the center of each cell in the box. * If that's less than
       best-so-far, update best distance and color number. */

    /* Nominal steps between cell centers ("x" in Thomas article) */
#define STEP_C0  ((1 << C0_SHIFT) * C0_SCALE)
#define STEP_C1  ((1 << C1_SHIFT) * C1_SCALE)
#define STEP_C2  ((1 << C2_SHIFT) * C2_SCALE)

    for (i = 0; i < numcolors; i++)
    {
	icolor = GETJSAMPLE(colorlist[i]);
	/* Compute (square of) distance from minc0/c1/c2 to this color */
	inc0 = (minc0 - GETJSAMPLE(sp->colormap[0][icolor])) * C0_SCALE;
	dist0 = inc0 * inc0;
	inc1 = (minc1 - GETJSAMPLE(sp->colormap[1][icolor])) * C1_SCALE;
	dist0 += inc1 * inc1;
	inc2 = (minc2 - GETJSAMPLE(sp->colormap[2][icolor])) * C2_SCALE;
	dist0 += inc2 * inc2;
	/* Form the initial difference increments */
	inc0 = inc0 * (2 * STEP_C0) + STEP_C0 * STEP_C0;
	inc1 = inc1 * (2 * STEP_C1) + STEP_C1 * STEP_C1;
	inc2 = inc2 * (2 * STEP_C2) + STEP_C2 * STEP_C2;
	/* Now loop over all cells in box, updating distance per Thomas
	   method */
	bptr = bestdist;
	cptr = bestcolor;
	xx0 = inc0;
	for (ic0 = BOX_C0_ELEMS - 1; ic0 >= 0; ic0--)
	{
	    dist1 = dist0;
	    xx1 = inc1;
	    for (ic1 = BOX_C1_ELEMS - 1; ic1 >= 0; ic1--)
	    {
		dist2 = dist1;
		xx2 = inc2;
		for (ic2 = BOX_C2_ELEMS - 1; ic2 >= 0; ic2--)
		{
		    if (dist2 < *bptr)
		    {
			*bptr = dist2;
			*cptr = (JSAMPLE) icolor;
		    }
		    dist2 += xx2;
		    xx2 += 2 * STEP_C2 * STEP_C2;
		    bptr++;
		    cptr++;
		}
		dist1 += xx1;
		xx1 += 2 * STEP_C1 * STEP_C1;
	    }
	    dist0 += xx0;
	    xx0 += 2 * STEP_C0 * STEP_C0;
	}
    }
}


LOCAL(void)
fill_inverse_cmap(SPEC *cquantize, int c0, int c1, int c2)
/* Fill the inverse-colormap entries in the update box that contains */
/* histogram cell c0/c1/c2.  (Only that one cell MUST be filled, but */
/* we can fill as many others as we wish.) */
{
    hist3d histogram = cquantize->histogram;
    int minc0, minc1, minc2;	/* lower left corner of update box */
    int ic0, ic1, ic2;
    register JSAMPLE *cptr;	/* pointer into bestcolor[] array */
    register histptr cachep;	/* pointer into main cache array */
    /* This array lists the candidate colormap indexes. */
    JSAMPLE colorlist[MAXNUMCOLORS];
    int numcolors;		/* number of candidate colors */
    /* This array holds the actually closest colormap index for each cell. */
    JSAMPLE bestcolor[BOX_C0_ELEMS * BOX_C1_ELEMS * BOX_C2_ELEMS];

    /* Convert cell coordinates to update box ID */
    c0 >>= BOX_C0_LOG;
    c1 >>= BOX_C1_LOG;
    c2 >>= BOX_C2_LOG;

    /* Compute true coordinates of update box's origin corner. * Actually we
       compute the coordinates of the center of the corner * histogram cell,
       which are the lower bounds of the volume we care about. */
    minc0 = (c0 << BOX_C0_SHIFT) + ((1 << C0_SHIFT) >> 1);
    minc1 = (c1 << BOX_C1_SHIFT) + ((1 << C1_SHIFT) >> 1);
    minc2 = (c2 << BOX_C2_SHIFT) + ((1 << C2_SHIFT) >> 1);

    /* Determine which colormap entries are close enough to be candidates *
       for the nearest entry to some cell in the update box. */
    numcolors = find_nearby_colors(cquantize, minc0, minc1, minc2, colorlist);

    /* Determine the actually nearest colors. */
    find_best_colors(cquantize, minc0, minc1, minc2, numcolors, colorlist,
		     bestcolor);

    /* Save the best color numbers (plus 1) in the main cache array */
    c0 <<= BOX_C0_LOG;		/* convert ID back to base cell indexes */
    c1 <<= BOX_C1_LOG;
    c2 <<= BOX_C2_LOG;
    cptr = bestcolor;
    for (ic0 = 0; ic0 < BOX_C0_ELEMS; ic0++)
    {
	for (ic1 = 0; ic1 < BOX_C1_ELEMS; ic1++)
	{
	    cachep = &histogram[c0 + ic0][c1 + ic1][c2];
	    for (ic2 = 0; ic2 < BOX_C2_ELEMS; ic2++)
	    {
		*cachep++ = (histcell) (GETJSAMPLE(*cptr++) + 1);
	    }
	}
    }
}

#define SHIFT_TEMPS   int shift_temp;
#define RIGHT_SHIFT(x,shft)   ((x) >> (shft))

METHODDEF(void)
pass2_fs_dither(SPEC *sp, unsigned char **red,
		unsigned char **green, unsigned char **blue,
		unsigned short **output_buf,
		int width, int num_rows)
/* This version performs Floyd-Steinberg dithering */
{
    hist3d histogram = sp->histogram;
    register LOCFSERROR cur0, cur1, cur2;	/* current error or pixel
						   value */
    LOCFSERROR belowerr0, belowerr1, belowerr2;		/* error for pixel
							   below cur */
    LOCFSERROR bpreverr0, bpreverr1, bpreverr2;		/* error for
							   below/prev col */
    register FSERRPTR errorptr;	/* => fserrors[] at column before current */
    unsigned short *outptr;	/* => current output pixel */
    histptr cachep;
    int dir;			/* +1 or -1 depending on direction */
    int dir3;			/* 3*dir, for advancing inptr & errorptr */
    int row;
    int col;
    int *error_limit = sp->error_limiter;
    int *colormap0 = sp->colormap[0];
    int *colormap1 = sp->colormap[1];
    int *colormap2 = sp->colormap[2];
    unsigned char *r, *g, *b;

    if (sp->im)
    {
        sp->im->completed = -1;
	sp->im->visual_cue(sp->im, "Dithering ...");
    }

    for (row = 0; row < num_rows; row++)
    {
	r = red[row];
	g = green[row];
	b = blue[row];
	outptr = output_buf[row];
	if (sp->on_odd_row)
	{
	    /* work right to left in this row */
	    r += width - 1;
	    g += width - 1;
	    b += width - 1;
	    outptr += width - 1;
	    dir = -1;
	    dir3 = -3;
	    errorptr = sp->fserrors + (width + 1) * 3;	/* => entry after
							   last column */
	    sp->on_odd_row = 0;	/* flip for next time */
	}
	else
	{
	    /* work left to right in this row */
	    dir = 1;
	    dir3 = 3;
	    errorptr = sp->fserrors;	/* => entry before first real column */
	    sp->on_odd_row = 1;	/* flip for next time */
	}
	/* Preset error values: no error propagated to first pixel from left */
	cur0 = cur1 = cur2 = 0;
	/* and no error propagated to row below yet */
	belowerr0 = belowerr1 = belowerr2 = 0;
	bpreverr0 = bpreverr1 = bpreverr2 = 0;

	for (col = 0; col < width; col++)
	{
	    /* curN holds the error propagated from the previous pixel on the
	       * current line.  Add the error propagated from the previous
	       line * to form the complete error correction term for this
	       pixel, and * round the error term (which is expressed * 16) to
	       an integer. * RIGHT_SHIFT rounds towards minus infinity, so
	       adding 8 is correct * for either sign of the error value. *
	       Note: errorptr points to *previous* column's array entry. */
	    cur0 = RIGHT_SHIFT(cur0 + errorptr[dir3 + 0] + 8, 4);
	    cur1 = RIGHT_SHIFT(cur1 + errorptr[dir3 + 1] + 8, 4);
	    cur2 = RIGHT_SHIFT(cur2 + errorptr[dir3 + 2] + 8, 4);
	    /* Limit the error using transfer function set by
	       init_error_limit. * See comments with init_error_limit for
	       rationale. */
	    cur0 = error_limit[cur0];
	    cur1 = error_limit[cur1];
	    cur2 = error_limit[cur2];
	    /* Form pixel value + error, and range-limit to 0..MAXJSAMPLE. *
	       The maximum error is +- MAXJSAMPLE (or less with error
	       limiting); * this sets the required size of the range_limit
	       array. */
	    cur0 += *r;
	    cur1 += *g;
	    cur2 += *b;


	    cur0 = FL_PCCLAMP(cur0);
	    cur1 = FL_PCCLAMP(cur1);
	    cur2 = FL_PCCLAMP(cur2);

	    /* Index into the cache with adjusted pixel value */
	    cachep = &histogram[cur0 >> C0_SHIFT][cur1 >> C1_SHIFT][cur2 >> C2_SHIFT];
	    /* If we have not seen this color before, find nearest colormap */
	    /* entry and update the cache */
	    if (*cachep == 0)
		fill_inverse_cmap(sp, cur0 >> C0_SHIFT, cur1 >> C1_SHIFT, cur2 >> C2_SHIFT);
	    /* Now emit the colormap index for this cell */
	    {
		register int pixcode = *cachep - 1;
		*outptr = (JSAMPLE) pixcode;

		/* Compute representation error for this pixel */
		cur0 -= colormap0[pixcode];
		cur1 -= colormap1[pixcode];
		cur2 -= colormap2[pixcode];
	    }

	    /* Compute error fractions to be propagated to adjacent pixels. * 
	       Add these into the running sums, and simultaneously shift the
	       * next-line error sums left by 1 column. */
	    {
		register LOCFSERROR bnexterr, delta;

		bnexterr = cur0;	/* Process component 0 */
		delta = cur0 * 2;
		cur0 += delta;	/* form error * 3 */
		errorptr[0] = (FSERROR) (bpreverr0 + cur0);
		cur0 += delta;	/* form error * 5 */
		bpreverr0 = belowerr0 + cur0;
		belowerr0 = bnexterr;
		cur0 += delta;	/* form error * 7 */
		bnexterr = cur1;	/* Process component 1 */
		delta = cur1 * 2;
		cur1 += delta;	/* form error * 3 */
		errorptr[1] = (FSERROR) (bpreverr1 + cur1);
		cur1 += delta;	/* form error * 5 */
		bpreverr1 = belowerr1 + cur1;
		belowerr1 = bnexterr;
		cur1 += delta;	/* form error * 7 */
		bnexterr = cur2;	/* Process component 2 */
		delta = cur2 * 2;
		cur2 += delta;	/* form error * 3 */
		errorptr[2] = (FSERROR) (bpreverr2 + cur2);
		cur2 += delta;	/* form error * 5 */
		bpreverr2 = belowerr2 + cur2;
		belowerr2 = bnexterr;
		cur2 += delta;	/* form error * 7 */
	    }

	    /* At this point curN contains the 7/16 error value to be
	       propagated * to the next pixel on the current line, and all
	       the errors for the * next line have been shifted over.  We are 
	       therefore ready to move on. */
	    r += dir;
	    g += dir;
	    b += dir;
	    outptr += dir;
	    errorptr += dir3;	/* advance errorptr to current column */
	}

	/* Post-loop cleanup: we must unload the final error values into the
	   * final fserrors[] entry.  Note we need not unload belowerrN
	   because * it is for the dummy column before or after the actual
	   array. */
	errorptr[0] = (FSERROR) bpreverr0;	/* unload prev errs into
						   array */
	errorptr[1] = (FSERROR) bpreverr1;
	errorptr[2] = (FSERROR) bpreverr2;
    }

    if(sp->im)
    {
       sp->im->completed = sp->im->total = sp->im->h;
       sp->im->visual_cue(sp->im, "Dithering done");
    }
}

LOCAL(void)
update_box(SPEC *sp, boxptr boxp)
/* Shrink the min/max bounds of a box to enclose only nonzero elements, */
/* and recompute its volume and population */
{
    hist3d histogram = sp->histogram;
    histptr histp;
    int c0, c1, c2;
    int c0min, c0max, c1min, c1max, c2min, c2max;
    int dist0, dist1, dist2;
    long ccount;

    c0min = boxp->c0min;
    c0max = boxp->c0max;
    c1min = boxp->c1min;
    c1max = boxp->c1max;
    c2min = boxp->c2min;
    c2max = boxp->c2max;

    if (c0max > c0min)
	for (c0 = c0min; c0 <= c0max; c0++)
	    for (c1 = c1min; c1 <= c1max; c1++)
	    {
		histp = &histogram[c0][c1][c2min];
		for (c2 = c2min; c2 <= c2max; c2++)
		    if (*histp++ != 0)
		    {
			boxp->c0min = c0min = c0;
			goto have_c0min;
		    }
	    }
  have_c0min:
    if (c0max > c0min)
	for (c0 = c0max; c0 >= c0min; c0--)
	    for (c1 = c1min; c1 <= c1max; c1++)
	    {
		histp = &histogram[c0][c1][c2min];
		for (c2 = c2min; c2 <= c2max; c2++)
		    if (*histp++ != 0)
		    {
			boxp->c0max = c0max = c0;
			goto have_c0max;
		    }
	    }
  have_c0max:
    if (c1max > c1min)
	for (c1 = c1min; c1 <= c1max; c1++)
	    for (c0 = c0min; c0 <= c0max; c0++)
	    {
		histp = &histogram[c0][c1][c2min];
		for (c2 = c2min; c2 <= c2max; c2++)
		    if (*histp++ != 0)
		    {
			boxp->c1min = c1min = c1;
			goto have_c1min;
		    }
	    }
  have_c1min:
    if (c1max > c1min)
	for (c1 = c1max; c1 >= c1min; c1--)
	    for (c0 = c0min; c0 <= c0max; c0++)
	    {
		histp = &histogram[c0][c1][c2min];
		for (c2 = c2min; c2 <= c2max; c2++)
		    if (*histp++ != 0)
		    {
			boxp->c1max = c1max = c1;
			goto have_c1max;
		    }
	    }
  have_c1max:
    if (c2max > c2min)
	for (c2 = c2min; c2 <= c2max; c2++)
	    for (c0 = c0min; c0 <= c0max; c0++)
	    {
		histp = &histogram[c0][c1min][c2];
		for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
		    if (*histp != 0)
		    {
			boxp->c2min = c2min = c2;
			goto have_c2min;
		    }
	    }
  have_c2min:
    if (c2max > c2min)
	for (c2 = c2max; c2 >= c2min; c2--)
	    for (c0 = c0min; c0 <= c0max; c0++)
	    {
		histp = &histogram[c0][c1min][c2];
		for (c1 = c1min; c1 <= c1max; c1++, histp += HIST_C2_ELEMS)
		    if (*histp != 0)
		    {
			boxp->c2max = c2max = c2;
			goto have_c2max;
		    }
	    }
  have_c2max:

    /* Update box volume. * We use 2-norm rather than real volume here; this
       biases the method * against making long narrow boxes, and it has the
       side benefit that * a box is splittable iff norm > 0. * Since the
       differences are expressed in histogram-cell units, * we have to shift
       back to JSAMPLE units to get consistent distances; * after which, we
       scale according to the selected distance scale factors. */
    dist0 = ((c0max - c0min) << C0_SHIFT) * C0_SCALE;
    dist1 = ((c1max - c1min) << C1_SHIFT) * C1_SCALE;
    dist2 = ((c2max - c2min) << C2_SHIFT) * C2_SCALE;
    boxp->volume = dist0 * dist0 + dist1 * dist1 + dist2 * dist2;

    /* Now scan remaining volume of box and compute population */
    ccount = 0;
    for (c0 = c0min; c0 <= c0max; c0++)
	for (c1 = c1min; c1 <= c1max; c1++)
	{
	    histp = &histogram[c0][c1][c2min];
	    for (c2 = c2min; c2 <= c2max; c2++, histp++)
		if (*histp != 0)
		{
		    ccount++;
		}
	}
    boxp->colorcount = ccount;
}

LOCAL(boxptr)
find_biggest_color_pop(boxptr boxlist, int numboxes)
/* Find the splittable box with the largest color population */
/* Returns NULL if no splittable boxes remain */
{
    register boxptr boxp;
    register int i;
    register long maxc = 0;
    boxptr which = NULL;

    for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++)
    {
	if (boxp->colorcount > maxc && boxp->volume > 0)
	{
	    which = boxp;
	    maxc = boxp->colorcount;
	}
    }
    return which;
}


LOCAL(boxptr)
find_biggest_volume(boxptr boxlist, int numboxes)
/* Find the splittable box with the largest (scaled) volume */
/* Returns NULL if no splittable boxes remain */
{
    register boxptr boxp;
    register int i;
    register int maxv = 0;
    boxptr which = NULL;

    for (i = 0, boxp = boxlist; i < numboxes; i++, boxp++)
    {
	if (boxp->volume > maxv)
	{
	    which = boxp;
	    maxv = boxp->volume;
	}
    }
    return which;
}

LOCAL(int)
median_cut(SPEC *sp, boxptr boxlist, int numboxes,
	   int desired_colors)
/* Repeatedly select and split the largest box until we have enough boxes */
{
    int n, lb;
    int c0, c1, c2, cmax;
    register boxptr b1, b2;

    while (numboxes < desired_colors)
    {
	/* Select box to split. * Current algorithm: by population for first
	   half, then by volume. */
	if (numboxes * 2 <= desired_colors)
	{
	    b1 = find_biggest_color_pop(boxlist, numboxes);
	}
	else
	{
	    b1 = find_biggest_volume(boxlist, numboxes);
	}
	if (b1 == NULL)		/* no splittable boxes left! */
	    break;
	b2 = &boxlist[numboxes];	/* where new box will go */
	/* Copy the color bounds to the new box. */
	b2->c0max = b1->c0max;
	b2->c1max = b1->c1max;
	b2->c2max = b1->c2max;
	b2->c0min = b1->c0min;
	b2->c1min = b1->c1min;
	b2->c2min = b1->c2min;
	/* Choose which axis to split the box on. * Current algorithm:
	   longest scaled axis. * See notes in update_box about scaling
	   distances. */
	c0 = ((b1->c0max - b1->c0min) << C0_SHIFT) * C0_SCALE;
	c1 = ((b1->c1max - b1->c1min) << C1_SHIFT) * C1_SCALE;
	c2 = ((b1->c2max - b1->c2min) << C2_SHIFT) * C2_SCALE;
	/* We want to break any ties in favor of green, then red, blue last.
	   * This code does the right thing for R,G,B or B,G,R color orders
	   only. */
#if RGB_RED == 0
	cmax = c1;
	n = 1;
	if (c0 > cmax)
	{
	    cmax = c0;
	    n = 0;
	}
	if (c2 > cmax)
	{
	    n = 2;
	}
#else
	cmax = c1;
	n = 1;
	if (c2 > cmax)
	{
	    cmax = c2;
	    n = 2;
	}
	if (c0 > cmax)
	{
	    n = 0;
	}
#endif
	/* Choose split point along selected axis, and update box bounds. *
	   Current algorithm: split at halfway point. * (Since the box has
	   been shrunk to minimum volume, * any split will produce two
	   nonempty subboxes.) * Note that lb value is max for lower box, so
	   must be < old max. */
	switch (n)
	{
	case 0:
	    lb = (b1->c0max + b1->c0min) / 2;
	    b1->c0max = lb;
	    b2->c0min = lb + 1;
	    break;
	case 1:
	    lb = (b1->c1max + b1->c1min) / 2;
	    b1->c1max = lb;
	    b2->c1min = lb + 1;
	    break;
	case 2:
	    lb = (b1->c2max + b1->c2min) / 2;
	    b1->c2max = lb;
	    b2->c2min = lb + 1;
	    break;
	}
	/* Update stats for boxes */
	update_box(sp, b1);
	update_box(sp, b2);
	numboxes++;
    }
    return numboxes;
}

LOCAL(void)
compute_color(SPEC *sp, boxptr boxp, int icolor)
/* Compute representative color for a box, put it in colormap[icolor] */
{
    /* Current algorithm: mean weighted by pixels (not colors) */
    /* Note it is important to get the rounding correct! */
    hist3d histogram = sp->histogram;
    histptr histp;
    int c0, c1, c2;
    int c0min, c0max, c1min, c1max, c2min, c2max;
    long count;
    long total = 0;
    long c0total = 0;
    long c1total = 0;
    long c2total = 0;

    c0min = boxp->c0min;
    c0max = boxp->c0max;
    c1min = boxp->c1min;
    c1max = boxp->c1max;
    c2min = boxp->c2min;
    c2max = boxp->c2max;

    for (c0 = c0min; c0 <= c0max; c0++)
	for (c1 = c1min; c1 <= c1max; c1++)
	{
	    histp = &histogram[c0][c1][c2min];
	    for (c2 = c2min; c2 <= c2max; c2++)
	    {
		if ((count = *histp++) != 0)
		{
		    total += count;
		    c0total += ((c0 << C0_SHIFT) + ((1 << C0_SHIFT) >> 1)) * count;
		    c1total += ((c1 << C1_SHIFT) + ((1 << C1_SHIFT) >> 1)) * count;
		    c2total += ((c2 << C2_SHIFT) + ((1 << C2_SHIFT) >> 1)) * count;
		}
	    }
	}

    sp->colormap[0][icolor] = (JSAMPLE) ((c0total + (total >> 1)) / total);
    sp->colormap[1][icolor] = (JSAMPLE) ((c1total + (total >> 1)) / total);
    sp->colormap[2][icolor] = (JSAMPLE) ((c2total + (total >> 1)) / total);
}

/* Master routine for color selection */
LOCAL(void)
select_colors(SPEC *sp, int desired_colors)
{
    boxptr boxlist;
    int numboxes;
    int i;

    if (sp->im)
	sp->im->visual_cue(sp->im, "Selecting Colors ...");

    /* Allocate workspace for box list */
    boxlist = fl_malloc(desired_colors * sizeof(box));
    /* Initialize one box containing whole space */
    numboxes = 1;
    boxlist[0].c0min = 0;
    boxlist[0].c0max = MAXJSAMPLE >> C0_SHIFT;
    boxlist[0].c1min = 0;
    boxlist[0].c1max = MAXJSAMPLE >> C1_SHIFT;
    boxlist[0].c2min = 0;
    boxlist[0].c2max = MAXJSAMPLE >> C2_SHIFT;
    /* Shrink it to actually-used volume and set its statistics */
    update_box(sp, &boxlist[0]);
    /* Perform median-cut to produce final box list */
    numboxes = median_cut(sp, boxlist, numboxes, desired_colors);
    /* Compute the representative color for each box, fill colormap */
    for (i = 0; i < numboxes; i++)
	compute_color(sp, &boxlist[i], i);
    sp->actual_number_of_colors = numboxes;
    fl_free(boxlist);
}


/* get histogram */
METHODDEF(void)
prescan_quantize(SPEC *sp, unsigned char **r, unsigned char **g,
		 unsigned char **b, int width, int num_rows)
{
    register histptr histp;
    register hist3d histogram = sp->histogram;
    int row, col;

    if (sp->im)
    {
	sp->im->completed = 0;
	sp->im->visual_cue(sp->im, "Getting Histogram ...");
    }

    for (row = 0; row < num_rows; row++)
    {
	for (col = width; --col >= 0;)
	{
	    /* get pixel value and index into the histogram */
	    histp = &histogram[r[row][col] >> C0_SHIFT]
		[g[row][col] >> C1_SHIFT]
		[b[row][col] >> C2_SHIFT];
	    /* increment, check for overflow and undo increment if so. */
	    if (++(*histp) <= 0)
		(*histp)--;
	}
    }
}

/*
 * Initialize the error-limiting transfer function (lookup table).
 * The raw F-S error computation can potentially compute error values of up to
 * +- MAXJSAMPLE.  But we want the maximum correction applied to a pixel to be
 * much less, otherwise obviously wrong pixels will be created.  (Typical
 * effects include weird fringes at color-area boundaries, isolated bright
 * pixels in a dark area, etc.)  The standard advice for avoiding this problem
 * is to ensure that the "corners" of the color cube are allocated as output
 * colors; then repeated errors in the same direction cannot cause cascading
 * error buildup.  However, that only prevents the error from getting
 * completely out of hand; Aaron Giles reports that error limiting improves
 * the results even with corner colors allocated.
 * A simple clamping of the error values to about +- MAXJSAMPLE/8 works pretty
 * well, but the smoother transfer function used below is even better.  Thanks
 * to Aaron Giles for this idea.
 */

LOCAL(void)
init_error_limit(SPEC *sp)
/* Allocate and fill in the error_limiter table */
{
    int *table;
    int in, out;

    table = fl_malloc((MAXJSAMPLE * 2 + 1) * sizeof(int));
    table += MAXJSAMPLE;	/* so can index -MAXJSAMPLE .. +MAXJSAMPLE */
    sp->error_limiter = table;

#define STEPSIZE ((MAXJSAMPLE+1)/16)
    /* Map errors 1:1 up to +- MAXJSAMPLE/16 */
    out = 0;
    for (in = 0; in < STEPSIZE; in++, out++)
    {
	table[in] = out;
	table[-in] = -out;
    }
    /* Map errors 1:2 up to +- 3*MAXJSAMPLE/16 */
    for (; in < STEPSIZE * 3; in++, out += (in & 1) ? 0 : 1)
    {
	table[in] = out;
	table[-in] = -out;
    }
    /* Clamp the rest to final out value (which is (MAXJSAMPLE+1)/8) */
    for (; in <= MAXJSAMPLE; in++)
    {
	table[in] = out;
	table[-in] = -out;
    }
#undef STEPSIZE
}