Pārlūkot izejas kodu

* blur.c: remove the blurring code and use our generic convolution

routine, which correctly recognises the Gaussian kernel as a separable
    filter. As a result, it is now 50% faster because the normalisation
    occurs at kernel build time.

git-svn-id: file:///srv/caca.zoy.org/var/lib/svn/libpipi/trunk@2661 92316355-f0b4-4df1-b90c-862c8a59935f
remotes/tiles
sam pirms 16 gadiem
vecāks
revīzija
8c4591f1d9
2 mainītis faili ar 26 papildinājumiem un 133 dzēšanām
  1. +26
    -131
      pipi/filter/blur.c
  2. +0
    -2
      pipi/filter/convolution.c

+ 26
- 131
pipi/filter/blur.c Parādīt failu

@@ -40,153 +40,48 @@ pipi_image_t *pipi_gaussian_blur(pipi_image_t *src, float radius)
pipi_image_t *pipi_gaussian_blur_ext(pipi_image_t *src, float rx, float ry,
float dx, float dy)
{
pipi_image_t *dst;
pipi_pixels_t *srcp, *dstp;
float *srcdata, *dstdata;
double *kernel, *buffer;
double K;
int x, y, i, w, h, kr, kw, gray;
pipi_image_t *ret;
double *kernel;
double Kx, Ky, t = 0.0;
int i, j, krx, kry, m, n;

if(rx < BLUR_EPSILON) rx = BLUR_EPSILON;
if(ry < BLUR_EPSILON) ry = BLUR_EPSILON;

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

gray = (src->last_modified == PIPI_PIXELS_Y_F);

srcp = gray ? pipi_getpixels(src, PIPI_PIXELS_Y_F)
: pipi_getpixels(src, PIPI_PIXELS_RGBA_F);
srcdata = (float *)srcp->pixels;

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

buffer = malloc(w * h * (gray ? 1 : 4) * sizeof(double));

/* FIXME: the kernel becomes far too big with large values of dx, because
* we grow both left and right. Fix the growing direction. */
kr = (int)(3. * rx + .99999 + ceil(abs(dx)));
kw = 2 * kr + 1;
K = -1. / (2. * rx * rx);
krx = (int)(3. * rx + .99999 + ceil(abs(dx)));
m = 2 * krx + 1;
Kx = -1. / (2. * rx * rx);

kry = (int)(3. * ry + .99999 + ceil(abs(dy)));
n = 2 * kry + 1;
Ky = -1. / (2. * ry * ry);

kernel = malloc(kw * sizeof(double));
for(i = -kr; i <= kr; i++)
kernel[i + kr] = exp(K * ((double)i + dx) * ((double)i + dx));
kernel = malloc(m * n * sizeof(double));

for(y = 0; y < h; y++)
for(j = -kry; j <= kry; j++)
{
for(x = 0; x < w; x++)
double ey = Ky * ((double)j + dy) * ((double)j + dy);

for(i = -krx; i <= krx; i++)
{
if(gray)
{
double Y = 0., t = 0.;
int x2;

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

x2 = x + i;
if(x2 < 0) x2 = 0;
else if(x2 >= w) x2 = w - 1;

Y += f * srcdata[y * w + x2];
t += f;
}

buffer[y * w + x] = Y / t;
}
else
{
double R = 0., G = 0., B = 0., t = 0.;
int x2, off = 4 * (y * w + x);

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

x2 = x + i;
if(x2 < 0) x2 = 0;
else if(x2 >= w) x2 = w - 1;

R += f * srcdata[(y * w + x2) * 4];
G += f * srcdata[(y * w + x2) * 4 + 1];
B += f * srcdata[(y * w + x2) * 4 + 2];
t += f;
}

buffer[off] = R / t;
buffer[off + 1] = G / t;
buffer[off + 2] = B / t;
}
double ex = Kx * ((double)i + dx) * ((double)i + dx);
double d = exp(ex + ey);

kernel[(j + kry) * m + i + krx] = d;
t += d;
}
}

free(kernel);

kr = (int)(3. * ry + .99999 + ceil(abs(dy)));
kw = 2 * kr + 1;
K = -1. / (2. * ry * ry);
for(j = 0; j < n; j++)
for(i = 0; i < m; i++)
kernel[j * m + i] /= t;

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

for(y = 0; y < h; y++)
{
for(x = 0; x < w; x++)
{
if(gray)
{
double Y = 0., t = 0.;
int y2;

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

y2 = y + i;
if(y2 < 0) y2 = 0;
else if(y2 >= h) y2 = h - 1;

Y += f * buffer[y2 * w + x];
t += f;
}

dstdata[y * w + x] = Y / t;
}
else
{
double R = 0., G = 0., B = 0., t = 0.;
int y2, off = 4 * (y * w + x);

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

y2 = y + i;
if(y2 < 0) y2 = 0;
else if(y2 >= h) y2 = h - 1;

R += f * buffer[(y2 * w + x) * 4];
G += f * buffer[(y2 * w + x) * 4 + 1];
B += f * buffer[(y2 * w + x) * 4 + 2];
t += f;
}

dstdata[off] = R / t;
dstdata[off + 1] = G / t;
dstdata[off + 2] = B / t;
}
}
}
ret = pipi_convolution(src, m, n, kernel);

free(buffer);
free(kernel);

return dst;
return ret;
}


+ 0
- 2
pipi/filter/convolution.c Parādīt failu

@@ -74,8 +74,6 @@ pipi_image_t *pipi_convolution(pipi_image_t *src, int m, int n, double mat[])
}
}

printf("separabble!\n");

/* Matrix rank is 1! Separate the filter */
/* FIXME: memleak */
hvec = malloc(m * sizeof(double));


Notiek ielāde…
Atcelt
Saglabāt