libpipi/pipi/filter/blur.c

/*
 *  libpipi       Proper image processing implementation library
 *  Copyright (c) 2004-2008 Sam Hocevar <sam@zoy.org>
 *                All Rights Reserved
 *
 *  $Id$
 *
 *  This library is free software. It comes without any warranty, to
 *  the extent permitted by applicable law. You can redistribute it
 *  and/or modify it under the terms of the Do What The Fuck You Want
 *  To Public License, Version 2, as published by Sam Hocevar. See
 *  http://sam.zoy.org/wtfpl/COPYING for more details.
 */

/*
 * blur.c: blur functions
 */

#include "config.h"
#include "common.h"

#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>

#include "pipi.h"
#include "pipi_internals.h"

pipi_image_t *pipi_gaussian_blur(pipi_image_t *src, float radius)
{
    pipi_image_t *dst;
    pipi_pixels_t *srcp, *dstp;
    float *srcdata, *dstdata;
    double *kernel;
    double K, L, t = 0.;
    int x, y, i, j, w, h, kr, kw;

    w = src->w;
    h = src->h;

    srcp = pipi_getpixels(src, PIPI_PIXELS_RGBA_F);
    srcdata = (float *)srcp->pixels;

    dst = pipi_new(w, h);
    dstp = pipi_getpixels(dst, PIPI_PIXELS_RGBA_F);
    dstdata = (float *)dstp->pixels;

    kr = (int)(3. * radius + 0.99999);
    kw = 2 * kr + 1;
    K = 1. / (2. * M_PI * radius * radius);
    L = -1. / (2. * radius * radius);

    kernel = malloc(kw * kw * sizeof(double));
    for(j = -kr; j <= kr; j++)
        for(i = -kr; i <= kr; i++)
            t += kernel[(j + kr) * kw + (i + kr)]
                     = exp(L * (i * i + j * j)) * K;

    for(j = -kr; j <= kr; j++)
        for(i = -kr; i <= kr; i++)
            kernel[(j + kr) * kw + (i + kr)] /= t;

    for(y = 0; y < h; y++)
    {
        for(x = 0; x < w; x++)
        {
            double R = 0., G = 0., B = 0.;

            for(j = -kr; j <= kr; j++)
                for(i = -kr; i <= kr; i++)
                {
                    double f = kernel[(j + kr) * kw + (i + kr)];

                    R += f * srcdata[((y + j) * w + x + i) * 4];
                    G += f * srcdata[((y + j) * w + x + i) * 4 + 1];
                    B += f * srcdata[((y + j) * w + x + i) * 4 + 2];
                }

            dstdata[(y * w + x) * 4] = R;
            dstdata[(y * w + x) * 4 + 1] = G;
            dstdata[(y * w + x) * 4 + 2] = B;
        }
    }

    return dst;
}