source: libpipi/trunk/examples/edd.c @ 2759

Last change on this file since 2759 was 2759, checked in by Sam Hocevar, 11 years ago
  • Get rid of the specific error diffusion functions, since our stock kernels work perfectly well.
File size: 3.0 KB
Line 
1/*
2 *  edd           error diffusion displacement
3 *  Copyright (c) 2008 Sam Hocevar <sam@zoy.org>
4 *                All Rights Reserved
5 *
6 *  $Id$
7 *
8 *  This program is free software. It comes without any warranty, to
9 *  the extent permitted by applicable law. You can redistribute it
10 *  and/or modify it under the terms of the Do What The Fuck You Want
11 *  To Public License, Version 2, as published by Sam Hocevar. See
12 *  http://sam.zoy.org/wtfpl/COPYING for more details.
13 */
14
15/* This program computes the Floyd-Steinberg error diffusion algorithm's
16 * displacement on the given input image. Error diffusion displacement is
17 * introduced in the paper "Reinstating Floyd-Steinberg: Improved Metrics
18 * for Quality Assessment of Error Diffusion Algorithms.", ICISP 2008
19 * Proceedings. Lecture Notes in Computer Science 5099 Springer 2008, ISBN
20 * 978-3-540-69904-0.
21 *
22 * The resulting dx/dy values are usually around 0.16/0.26 for images that
23 * are not entirely black and white. */
24
25#include "config.h"
26#include "common.h"
27
28#include <stdio.h>
29#include <stdlib.h>
30#include <string.h>
31
32#include <pipi.h>
33
34#define Z 3
35
36int main(int argc, char *argv[])
37{
38    double sigma = 1.2, precision = 0.001, step = 2.;
39    double best = 1., fx = -1., fy = -1., bfx = 0., bfy = 0.;
40    double e, e0, e1;
41    pipi_image_t *img, *kernel, *gauss, *dither, *tmp;
42    int dx, dy;
43
44    if(argc < 2)
45    {
46        fprintf(stderr, "%s: too few arguments\n", argv[0]);
47        fprintf(stderr, "Usage: %s <image>\n", argv[0]);
48        return EXIT_FAILURE;
49    }
50
51    /* Load image, convert it to grayscale, dither it with Floyd-Steinberg */
52    img = pipi_load(argv[1]);
53    pipi_getpixels(img, PIPI_PIXELS_Y_F);
54    gauss = pipi_gaussian_blur(img, sigma);
55    kernel = pipi_load("ediff:fs");
56    dither = pipi_dither_ediff(img, kernel, PIPI_SCAN_RASTER);
57    pipi_free(kernel);
58    pipi_free(img);
59
60    /* Compute the standard error */
61    tmp = pipi_gaussian_blur(dither, sigma);
62    e0 = pipi_measure_msd(gauss, tmp);
63    pipi_free(tmp);
64
65    /* Compute the fast error */
66    tmp = pipi_gaussian_blur_ext(dither, sigma, sigma, 0.0, 0.16, 0.26);
67    e1 = pipi_measure_msd(gauss, tmp);
68    pipi_free(tmp);
69
70    /* Compute displacement */
71    while(step > precision)
72    {
73        for(dy = 0; dy <= Z; dy++)
74            for(dx = 0; dx <= Z; dx++)
75            {
76                tmp = pipi_gaussian_blur_ext(dither, sigma, sigma, 0.0,
77                                             fx + step * dx / Z,
78                                             fy + step * dy / Z);
79                e = pipi_measure_msd(gauss, tmp);
80                pipi_free(tmp);
81                if(e < best)
82                {
83                    best = e;
84                    bfx = fx + step * dx / Z;
85                    bfy = fy + step * dy / Z;
86                }
87            }
88
89        fx = bfx - step / Z;
90        fy = bfy - step / Z;
91        step = step * 2 / Z;
92    }
93
94    printf("E: %g E_fast: %g E_min: %g dx: %g dy: %g\n", e0, e1, best, fx, fy);
95
96    pipi_free(dither);
97    pipi_free(gauss);
98
99    return 0;
100}
101
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