/*!
* pixBilateralGrayExact()
*
* Input: pixs (8 bpp gray)
* spatial_kel (gaussian kernel)
* range_kel (<optional> 256 x 1, monotonically decreasing)
* Return: pixd (8 bpp bilateral filtered image)
*
* Notes:
* (1) See pixBilateralExact().
*/
PIX *
pixBilateralGrayExact(PIX *pixs,
L_KERNEL *spatial_kel,
L_KERNEL *range_kel) {
l_int32 i, j, id, jd, k, m, w, h, d, sx, sy, cx, cy, wplt, wpld;
l_int32 val, center_val;
l_uint32 *datat, *datad, *linet, *lined;
l_float32 sum, weight_sum, weight;
L_KERNEL *keli;
PIX *pixt, *pixd;
PROCNAME("pixBilateralGrayExact");
if (!pixs)
return (PIX *) ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetDepth(pixs) != 8)
return (PIX *) ERROR_PTR("pixs must be gray", procName, NULL);
pixGetDimensions(pixs, &w, &h, &d);
if (!spatial_kel)
return (PIX *) ERROR_PTR("spatial kel not defined", procName, NULL);
if (!range_kel)
return pixConvolve(pixs, spatial_kel, 8, 1);
if (range_kel->sx != 256 || range_kel->sy != 1)
return (PIX *) ERROR_PTR("range kel not {256 x 1", procName, NULL);
keli = kernelInvert(spatial_kel);
kernelGetParameters(keli, &sy, &sx, &cy, &cx);
if ((pixt = pixAddMirroredBorder(pixs, cx, sx - cx, cy, sy - cy)) == NULL)
return (PIX *) ERROR_PTR("pixt not made", procName, NULL);
pixd = pixCreate(w, h, 8);
datat = pixGetData(pixt);
datad = pixGetData(pixd);
wplt = pixGetWpl(pixt);
wpld = pixGetWpl(pixd);
for (i = 0, id = 0; id < h; i++, id++) {
lined = datad + id * wpld;
for (j = 0, jd = 0; jd < w; j++, jd++) {
center_val = GET_DATA_BYTE(datat + (i + cy) * wplt, j + cx);
weight_sum = 0.0;
sum = 0.0;
for (k = 0; k < sy; k++) {
linet = datat + (i + k) * wplt;
for (m = 0; m < sx; m++) {
val = GET_DATA_BYTE(linet, j + m);
weight = keli->data[k][m] *
range_kel->data[0][L_ABS(center_val - val)];
weight_sum += weight;
sum += val * weight;
}
}
SET_DATA_BYTE(lined, jd, (l_int32)(sum / weight_sum + 0.5));
}
}
kernelDestroy(&keli);
pixDestroy(&pixt);
return pixd;
}
/*!
* pixAdaptiveMeanFilter()
*
* Input: pixs (8 bpp grayscale)
* wc, hc (half width/height of convolution kernel)
* varn (value of overall noise variance)
* Return: pixd (8 bpp, filtered image)
*
* Notes:
* (1) The filter reduces gaussian noise, achieving results similar
* to the arithmetic and geometric mean filters but avoiding the
* considerable image blurring effect introduced by those filters.
* (2) The filter can be expressed mathematically by:
* f'(x, y) = g(x, y) - varN / varL * [ g(x, y) - meanL ]
* where:
* -- g(x, y) is the pixel at the center of local region S of
* width (2 * wc + 1) and height (2 * wh + 1)
* -- varN and varL are the overall noise variance (given in input)
* and local variance of S, respectively
* -- meanL is the local mean of S
* (3) Typically @varn is estimated by studying the PDFs produced by
* the camera or equipment sensors.
*/
PIX *
pixAdaptiveMeanFilter(PIX *pixs,
l_int32 wc,
l_int32 hc,
l_float32 varn)
{
l_int32 i, j, w, h, d, wplt, wpld, wincr, hincr;
l_uint32 val;
l_uint32 *datat, *datad, *linet, *lined;
l_float32 norm, meanl, varl, ratio;
PIX *pixt, *pixd;
PROCNAME("pixAdaptiveMeanFilter");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
pixGetDimensions(pixs, &w, &h, &d);
if (d != 8)
return (PIX *)ERROR_PTR("pixs not 8 bpp", procName, NULL);
if (wc < 1 || hc < 1)
return (PIX *)ERROR_PTR("wc and hc not >= 1", procName, NULL);
/* Add wc to each side, and hc to top and bottom of the image,
* mirroring for accuracy and to avoid special-casing the boundary. */
if ((pixt = pixAddMirroredBorder(pixs, wc, wc, hc, hc)) == NULL)
return (PIX *)ERROR_PTR("pixt not made", procName, NULL);
/* Place the filter center at (0, 0). This is just a
* convenient location, because it allows us to perform
* the filtering over x:(0 ... w - 1) and y:(0 ... h - 1). */
pixd = pixCreateTemplate(pixs);
wplt = pixGetWpl(pixt);
wpld = pixGetWpl(pixd);
datat = pixGetData(pixt);
datad = pixGetData(pixd);
wincr = 2 * wc + 1;
hincr = 2 * hc + 1;
norm = 1.0 / (wincr * hincr);
for (i = 0; i < h; i++) {
linet = datat + (i + hc) * wplt;
lined = datad + i * wpld;
for (j = 0; j < w; j++) {
/* Calculate mean intensity value */
meanl = calculateLocalMeanLow(datat, wplt, wincr, hincr, i, j);
/* Calculate local variance */
varl = calculateLocalVarianceLow(datat, wplt, wincr, hincr, i, j, meanl);
/* Account for special case in which varN is more than varL */
ratio = (varn > varl) ? 1 : varn / varl;
val = GET_DATA_BYTE(linet, j + wc);
SET_DATA_BYTE(lined, j, (l_uint8) (val - ratio * (val - meanl)));
}
}
pixDestroy(&pixt);
return pixd;
}
main(int argc,
char **argv)
{
l_int32 i, j, equal;
PIX *pixs, *pixt, *pixd;
static char mainName[] = "rasteropip_reg";
pixs = pixRead("test8.jpg");
pixt = pixCopy(NULL, pixs);
/* Copy, in-place and one COLUMN at a time, from the right
side to the left side. */
for (j = 0; j < 200; j++)
pixRasterop(pixs, 20 + j, 20, 1, 250, PIX_SRC, pixs, 250 + j, 20);
pixDisplay(pixs, 50, 50);
/* Copy, in-place and one ROW at a time, from the right
side to the left side. */
for (i = 0; i < 250; i++)
pixRasterop(pixt, 20, 20 + i, 200, 1, PIX_SRC, pixt, 250, 20 + i);
pixDisplay(pixt, 620, 50);
/* Test */
pixEqual(pixs, pixt, &equal);
if (equal)
fprintf(stderr, "OK: images are the same\n");
else
fprintf(stderr, "Error: images are different\n");
pixWrite("/tmp/junkpix.png", pixs, IFF_PNG);
pixDestroy(&pixs);
pixDestroy(&pixt);
/* Show the mirrored border, which uses the general
pixRasterop() on an image in-place. */
pixs = pixRead("test8.jpg");
pixt = pixRemoveBorder(pixs, 40);
pixd = pixAddMirroredBorder(pixt, 25, 25, 25, 25);
pixDisplay(pixd, 50, 550);
pixDestroy(&pixs);
pixDestroy(&pixt);
pixDestroy(&pixd);
return 0;
}
main(int argc,
char **argv)
{
l_int32 i, j;
PIX *pixs, *pixt, *pixd;
L_REGPARAMS *rp;
if (regTestSetup(argc, argv, &rp))
return 1;
pixs = pixRead("test8.jpg");
pixt = pixCopy(NULL, pixs);
/* Copy, in-place and one COLUMN at a time, from the right
side to the left side. */
for (j = 0; j < 200; j++)
pixRasterop(pixs, 20 + j, 20, 1, 250, PIX_SRC, pixs, 250 + j, 20);
pixDisplayWithTitle(pixs, 50, 50, "in-place copy", rp->display);
/* Copy, in-place and one ROW at a time, from the right
side to the left side. */
for (i = 0; i < 250; i++)
pixRasterop(pixt, 20, 20 + i, 200, 1, PIX_SRC, pixt, 250, 20 + i);
/* Test */
regTestComparePix(rp, pixs, pixt); /* 0 */
pixDestroy(&pixs);
pixDestroy(&pixt);
/* Show the mirrored border, which uses the general
pixRasterop() on an image in-place. */
pixs = pixRead("test8.jpg");
pixt = pixRemoveBorder(pixs, 40);
pixd = pixAddMirroredBorder(pixt, 40, 40, 40, 40);
regTestWritePixAndCheck(rp, pixd, IFF_PNG); /* 1 */
pixDisplayWithTitle(pixd, 650, 50, "mirrored border", rp->display);
pixDestroy(&pixs);
pixDestroy(&pixt);
pixDestroy(&pixd);
return regTestCleanup(rp);
}
/*!
* pixSauvolaBinarize()
*
* Input: pixs (8 bpp grayscale; not colormapped)
* whsize (window half-width for measuring local statistics)
* factor (factor for reducing threshold due to variance; >= 0)
* addborder (1 to add border of width (@whsize + 1) on all sides)
* &pixm (<optional return> local mean values)
* &pixsd (<optional return> local standard deviation values)
* &pixth (<optional return> threshold values)
* &pixd (<optional return> thresholded image)
* Return: 0 if OK, 1 on error
*
* Notes:
* (1) The window width and height are 2 * @whsize + 1. The minimum
* value for @whsize is 2; typically it is >= 7..
* (2) The local statistics, measured over the window, are the
* average and standard deviation.
* (3) The measurements of the mean and standard deviation are
* performed inside a border of (@whsize + 1) pixels. If pixs does
* not have these added border pixels, use @addborder = 1 to add
* it here; otherwise use @addborder = 0.
* (4) The Sauvola threshold is determined from the formula:
* t = m * (1 - k * (1 - s / 128))
* where:
* t = local threshold
* m = local mean
* k = @factor (>= 0) [ typ. 0.35 ]
* s = local standard deviation, which is maximized at
* 127.5 when half the samples are 0 and half are 255.
* (5) The basic idea of Niblack and Sauvola binarization is that
* the local threshold should be less than the median value,
* and the larger the variance, the closer to the median
* it should be chosen. Typical values for k are between
* 0.2 and 0.5.
*/
l_int32
pixSauvolaBinarize(PIX *pixs,
l_int32 whsize,
l_float32 factor,
l_int32 addborder,
PIX **ppixm,
PIX **ppixsd,
PIX **ppixth,
PIX **ppixd)
{
l_int32 w, h;
PIX *pixg, *pixsc, *pixm, *pixms, *pixth, *pixd;
PROCNAME("pixSauvolaBinarize");
if (!ppixm && !ppixsd && !ppixth && !ppixd)
return ERROR_INT("no outputs", procName, 1);
if (ppixm) *ppixm = NULL;
if (ppixsd) *ppixsd = NULL;
if (ppixth) *ppixth = NULL;
if (ppixd) *ppixd = NULL;
if (!pixs || pixGetDepth(pixs) != 8)
return ERROR_INT("pixs undefined or not 8 bpp", procName, 1);
if (pixGetColormap(pixs))
return ERROR_INT("pixs is cmapped", procName, 1);
pixGetDimensions(pixs, &w, &h, NULL);
if (whsize < 2)
return ERROR_INT("whsize must be >= 2", procName, 1);
if (w < 2 * whsize + 3 || h < 2 * whsize + 3)
return ERROR_INT("whsize too large for image", procName, 1);
if (factor < 0.0)
return ERROR_INT("factor must be >= 0", procName, 1);
if (addborder) {
pixg = pixAddMirroredBorder(pixs, whsize + 1, whsize + 1,
whsize + 1, whsize + 1);
pixsc = pixClone(pixs);
} else {
pixg = pixClone(pixs);
pixsc = pixRemoveBorder(pixs, whsize + 1);
}
if (!pixg || !pixsc)
return ERROR_INT("pixg and pixsc not made", procName, 1);
/* All these functions strip off the border pixels. */
if (ppixm || ppixth || ppixd)
pixm = pixWindowedMean(pixg, whsize, whsize, 1, 1);
if (ppixsd || ppixth || ppixd)
pixms = pixWindowedMeanSquare(pixg, whsize, whsize, 1);
if (ppixth || ppixd)
pixth = pixSauvolaGetThreshold(pixm, pixms, factor, ppixsd);
if (ppixd)
pixd = pixApplyLocalThreshold(pixsc, pixth, 1);
if (ppixm)
*ppixm = pixm;
else
pixDestroy(&pixm);
pixDestroy(&pixms);
if (ppixth)
*ppixth = pixth;
else
pixDestroy(&pixth);
if (ppixd)
*ppixd = pixd;
else
pixDestroy(&pixd);
pixDestroy(&pixg);
pixDestroy(&pixsc);
return 0;
}
/*!
* bilateralCreate()
*
* Input: pixs (8 bpp gray, no colormap)
* spatial_stdev (of gaussian kernel; in pixels, > 0.5)
* range_stdev (of gaussian range kernel; > 5.0; typ. 50.0)
* ncomps (number of intermediate sums J(k,x); in [4 ... 30])
* reduction (1, 2 or 4)
* Return: bil, or null on error
*
* Notes:
* (1) This initializes a bilateral filtering operation, generating all
* the data required. It takes most of the time in the bilateral
* filtering operation.
* (2) See bilateral.h for details of the algorithm.
* (3) See pixBilateral() for constraints on input parameters, which
* are not checked here.
*/
static L_BILATERAL *
bilateralCreate(PIX *pixs,
l_float32 spatial_stdev,
l_float32 range_stdev,
l_int32 ncomps,
l_int32 reduction) {
l_int32 w, ws, wd, h, hs, hd, i, j, k, index;
l_int32 border, minval, maxval, spatial_size;
l_int32 halfwidth, wpls, wplt, wpld, kval, nval, dval;
l_float32 sstdev, fval1, fval2, denom, sum, norm, kern;
l_int32 *nc, *kindex;
l_float32 *kfract, *range, *spatial;
l_uint32 *datas, *datat, *datad, *lines, *linet, *lined;
L_BILATERAL *bil;
PIX *pixt, *pixt2, *pixsc, *pixd;
PIXA *pixac;
PROCNAME("bilateralCreate");
sstdev = spatial_stdev / (l_float32) reduction; /* reduced spat. stdev */
if ((bil = (L_BILATERAL *) CALLOC(1, sizeof(L_BILATERAL))) == NULL)
return (L_BILATERAL *) ERROR_PTR("bil not made", procName, NULL);
bil->spatial_stdev = sstdev;
bil->range_stdev = range_stdev;
bil->reduction = reduction;
bil->ncomps = ncomps;
if (reduction == 1) {
pixt = pixClone(pixs);
} else if (reduction == 2) {
pixt = pixScaleAreaMap2(pixs);
} else { /* reduction == 4) */
pixt2 = pixScaleAreaMap2(pixs);
pixt = pixScaleAreaMap2(pixt2);
pixDestroy(&pixt2);
}
pixGetExtremeValue(pixt, 1, L_SELECT_MIN, NULL, NULL, NULL, &minval);
pixGetExtremeValue(pixt, 1, L_SELECT_MAX, NULL, NULL, NULL, &maxval);
bil->minval = minval;
bil->maxval = maxval;
border = (l_int32)(2 * sstdev + 1);
pixsc = pixAddMirroredBorder(pixt, border, border, border, border);
bil->pixsc = pixsc;
pixDestroy(&pixt);
bil->pixs = pixClone(pixs);
/* -------------------------------------------------------------------- *
* Generate arrays for interpolation of J(k,x):
* (1.0 - kfract[.]) * J(kindex[.], x) + kfract[.] * J(kindex[.] + 1, x),
* where I(x) is the index into kfract[] and kindex[],
* and x is an index into the 2D image array.
* -------------------------------------------------------------------- */
/* nc is the set of k values to be used in J(k,x) */
nc = (l_int32 *) CALLOC(ncomps, sizeof(l_int32));
for (i = 0; i < ncomps; i++)
nc[i] = minval + i * (maxval - minval) / (ncomps - 1);
bil->nc = nc;
/* kindex maps from intensity I(x) to the lower k index for J(k,x) */
kindex = (l_int32 *) CALLOC(256, sizeof(l_int32));
for (i = minval, k = 0; i <= maxval && k < ncomps - 1; k++) {
fval2 = nc[k + 1];
while (i < fval2) {
kindex[i] = k;
i++;
}
}
kindex[maxval] = ncomps - 2;
bil->kindex = kindex;
/* kfract maps from intensity I(x) to the fraction of J(k+1,x) used */
kfract = (l_float32 *) CALLOC(256, sizeof(l_float32)); /* from lower */
for (i = minval, k = 0; i <= maxval && k < ncomps - 1; k++) {
fval1 = nc[k];
fval2 = nc[k + 1];
while (i < fval2) {
kfract[i] = (l_float32)(i - fval1) / (l_float32)(fval2 - fval1);
i++;
}
}
kfract[maxval] = 1.0;
bil->kfract = kfract;
#if DEBUG_BILATERAL
for (i = minval; i <= maxval; i++)
fprintf(stderr, "kindex[%d] = %d; kfract[%d] = %5.3f\n",
i, kindex[i], i, kfract[i]);
for (i = 0; i < ncomps; i++)
fprintf(stderr, "nc[%d] = %d\n", i, nc[i]);
#endif /* DEBUG_BILATERAL */
/* -------------------------------------------------------------------- *
* Generate 1-D kernel arrays (spatial and range) *
* -------------------------------------------------------------------- */
spatial_size = 2 * sstdev + 1;
spatial = (l_float32 *) CALLOC(spatial_size, sizeof(l_float32));
denom = 2. * sstdev * sstdev;
for (i = 0; i < spatial_size; i++)
spatial[i] = expf(-(l_float32)(i * i) / denom);
bil->spatial = spatial;
range = (l_float32 *) CALLOC(256, sizeof(l_float32));
denom = 2. * range_stdev * range_stdev;
for (i = 0; i < 256; i++)
range[i] = expf(-(l_float32)(i * i) / denom);
bil->range = range;
/* -------------------------------------------------------------------- *
* Generate principal bilateral component images *
* -------------------------------------------------------------------- */
pixac = pixaCreate(ncomps);
pixGetDimensions(pixsc, &ws, &hs, NULL);
datas = pixGetData(pixsc);
wpls = pixGetWpl(pixsc);
pixGetDimensions(pixs, &w, &h, NULL);
wd = (w + reduction - 1) / reduction;
hd = (h + reduction - 1) / reduction;
halfwidth = (l_int32)(2.0 * sstdev);
for (index = 0; index < ncomps; index++) {
pixt = pixCopy(NULL, pixsc);
datat = pixGetData(pixt);
wplt = pixGetWpl(pixt);
kval = nc[index];
/* Separable convolutions: horizontal first */
for (i = 0; i < hd; i++) {
lines = datas + (border + i) * wpls;
linet = datat + (border + i) * wplt;
for (j = 0; j < wd; j++) {
sum = 0.0;
norm = 0.0;
for (k = -halfwidth; k <= halfwidth; k++) {
nval = GET_DATA_BYTE(lines, border + j + k);
kern = spatial[L_ABS(k)] * range[L_ABS(kval - nval)];
sum += kern * nval;
norm += kern;
}
dval = (l_int32)((sum / norm) + 0.5);
SET_DATA_BYTE(linet, border + j, dval);
}
}
/* Vertical convolution */
pixd = pixCreate(wd, hd, 8);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
for (i = 0; i < hd; i++) {
linet = datat + (border + i) * wplt;
lined = datad + i * wpld;
for (j = 0; j < wd; j++) {
sum = 0.0;
norm = 0.0;
for (k = -halfwidth; k <= halfwidth; k++) {
nval = GET_DATA_BYTE(linet + k * wplt, border + j);
kern = spatial[L_ABS(k)] * range[L_ABS(kval - nval)];
sum += kern * nval;
norm += kern;
}
dval = (l_int32)((sum / norm) + 0.5);
SET_DATA_BYTE(lined, j, dval);
}
}
pixDestroy(&pixt);
pixaAddPix(pixac, pixd, L_INSERT);
}
bil->pixac = pixac;
bil->lineset = (l_uint32 ***) pixaGetLinePtrs(pixac, NULL);
return bil;
}
/*!
* \brief pixTilingGetTile()
*
* \param[in] pt pixtiling
* \param[in] i tile row index
* \param[in] j tile column index
* \return pixd tile with appropriate boundary (overlap) pixels added,
* or NULL on error
*/
PIX *
pixTilingGetTile(PIXTILING *pt,
l_int32 i,
l_int32 j)
{
l_int32 wpix, hpix, wt, ht, nx, ny;
l_int32 xoverlap, yoverlap, wtlast, htlast;
l_int32 left, top, xtraleft, xtraright, xtratop, xtrabot, width, height;
BOX *box;
PIX *pixs, *pixt, *pixd;
PROCNAME("pixTilingGetTile");
if (!pt)
return (PIX *)ERROR_PTR("pt not defined", procName, NULL);
if ((pixs = pt->pix) == NULL)
return (PIX *)ERROR_PTR("pix not found", procName, NULL);
pixTilingGetCount(pt, &nx, &ny);
if (i < 0 || i >= ny)
return (PIX *)ERROR_PTR("invalid row index i", procName, NULL);
if (j < 0 || j >= nx)
return (PIX *)ERROR_PTR("invalid column index j", procName, NULL);
/* Grab the tile with as much overlap as exists within the
* input pix. First, compute the (left, top) coordinates. */
pixGetDimensions(pixs, &wpix, &hpix, NULL);
pixTilingGetSize(pt, &wt, &ht);
xoverlap = pt->xoverlap;
yoverlap = pt->yoverlap;
wtlast = wpix - wt * (nx - 1);
htlast = hpix - ht * (ny - 1);
left = L_MAX(0, j * wt - xoverlap);
top = L_MAX(0, i * ht - yoverlap);
/* Get the width and height of the tile, including whatever
* overlap is available. */
if (nx == 1)
width = wpix;
else if (j == 0)
width = wt + xoverlap;
else if (j == nx - 1)
width = wtlast + xoverlap;
else
width = wt + 2 * xoverlap;
if (ny == 1)
height = hpix;
else if (i == 0)
height = ht + yoverlap;
else if (i == ny - 1)
height = htlast + yoverlap;
else
height = ht + 2 * yoverlap;
box = boxCreate(left, top, width, height);
pixt = pixClipRectangle(pixs, box, NULL);
boxDestroy(&box);
/* If no overlap, do not add any special case borders */
if (xoverlap == 0 && yoverlap == 0)
return pixt;
/* Add overlap as a mirrored border, in the 8 special cases where
* the tile touches the border of the input pix. The xtratop (etc)
* parameters are required where the tile is either full width
* or full height. */
xtratop = xtrabot = xtraleft = xtraright = 0;
if (nx == 1)
xtraleft = xtraright = xoverlap;
if (ny == 1)
xtratop = xtrabot = yoverlap;
if (i == 0 && j == 0)
pixd = pixAddMirroredBorder(pixt, xoverlap, xtraright,
yoverlap, xtrabot);
else if (i == 0 && j == nx - 1)
pixd = pixAddMirroredBorder(pixt, xtraleft, xoverlap,
yoverlap, xtrabot);
else if (i == ny - 1 && j == 0)
pixd = pixAddMirroredBorder(pixt, xoverlap, xtraright,
xtratop, yoverlap);
else if (i == ny - 1 && j == nx - 1)
pixd = pixAddMirroredBorder(pixt, xtraleft, xoverlap,
xtratop, yoverlap);
else if (i == 0)
pixd = pixAddMirroredBorder(pixt, 0, 0, yoverlap, xtrabot);
else if (i == ny - 1)
pixd = pixAddMirroredBorder(pixt, 0, 0, xtratop, yoverlap);
else if (j == 0)
pixd = pixAddMirroredBorder(pixt, xoverlap, xtraright, 0, 0);
else if (j == nx - 1)
pixd = pixAddMirroredBorder(pixt, xtraleft, xoverlap, 0, 0);
else
pixd = pixClone(pixt);
pixDestroy(&pixt);
return pixd;
}
int main(int argc,
char **argv)
{
FPIX *fpix1, *fpix2, *fpix3, *fpix4;
PIX *pix1, *pix2, *pix3, *pix4, *pix5, *pix6, *pix7, *pix8;
L_REGPARAMS *rp;
if (regTestSetup(argc, argv, &rp))
return 1;
/* Test orthogonal rotations */
pix1 = pixRead("marge.jpg");
pix2 = pixConvertTo8(pix1, 0);
fpix1 = pixConvertToFPix(pix2, 1);
fpix2 = fpixRotateOrth(fpix1, 1);
pix3 = fpixConvertToPix(fpix2, 8, L_CLIP_TO_ZERO, 0);
pix4 = pixRotateOrth(pix2, 1);
regTestComparePix(rp, pix3, pix4); /* 0 */
pixDisplayWithTitle(pix3, 100, 100, NULL, rp->display);
fpix3 = fpixRotateOrth(fpix1, 2);
pix5 = fpixConvertToPix(fpix3, 8, L_CLIP_TO_ZERO, 0);
pix6 = pixRotateOrth(pix2, 2);
regTestComparePix(rp, pix5, pix6); /* 1 */
pixDisplayWithTitle(pix5, 560, 100, NULL, rp->display);
fpix4 = fpixRotateOrth(fpix1, 3);
pix7 = fpixConvertToPix(fpix4, 8, L_CLIP_TO_ZERO, 0);
pix8 = pixRotateOrth(pix2, 3);
regTestComparePix(rp, pix7, pix8); /* 2 */
pixDisplayWithTitle(pix7, 1170, 100, NULL, rp->display);
pixDisplayWithTitle(pix2, 560, 580, NULL, rp->display);
pixDestroy(&pix1);
pixDestroy(&pix2);
pixDestroy(&pix3);
pixDestroy(&pix4);
pixDestroy(&pix5);
pixDestroy(&pix6);
pixDestroy(&pix7);
pixDestroy(&pix8);
fpixDestroy(&fpix1);
fpixDestroy(&fpix2);
fpixDestroy(&fpix3);
fpixDestroy(&fpix4);
/* Test adding various borders */
pix1 = pixRead("marge.jpg");
pix2 = pixConvertTo8(pix1, 0);
fpix1 = pixConvertToFPix(pix2, 1);
fpix2 = fpixAddMirroredBorder(fpix1, 21, 21, 25, 25);
pix3 = fpixConvertToPix(fpix2, 8, L_CLIP_TO_ZERO, 0);
pix4 = pixAddMirroredBorder(pix2, 21, 21, 25, 25);
regTestComparePix(rp, pix3, pix4); /* 3 */
pixDisplayWithTitle(pix3, 100, 1000, NULL, rp->display);
fpix3 = fpixAddContinuedBorder(fpix1, 21, 21, 25, 25);
pix5 = fpixConvertToPix(fpix3, 8, L_CLIP_TO_ZERO, 0);
pix6 = pixAddContinuedBorder(pix2, 21, 21, 25, 25);
regTestComparePix(rp, pix5, pix6); /* 4 */
pixDisplayWithTitle(pix5, 750, 1000, NULL, rp->display);
pixDestroy(&pix1);
pixDestroy(&pix2);
pixDestroy(&pix3);
pixDestroy(&pix4);
pixDestroy(&pix5);
pixDestroy(&pix6);
fpixDestroy(&fpix1);
fpixDestroy(&fpix2);
fpixDestroy(&fpix3);
return regTestCleanup(rp);
}
/*!
* pixRankFilterGray()
*
* Input: pixs (8 bpp; no colormap)
* wf, hf (width and height of filter; each is >= 1)
* rank (in [0.0 ... 1.0])
* Return: pixd (of rank values), or null on error
*
* Notes:
* (1) This defines, for each pixel in pixs, a neighborhood of
* pixels given by a rectangle "centered" on the pixel.
* This set of wf*hf pixels has a distribution of values,
* and if they are sorted in increasing order, we choose
* the pixel such that rank*(wf*hf-1) pixels have a lower
* or equal value and (1-rank)*(wf*hf-1) pixels have an equal
* or greater value.
* (2) By this definition, the rank = 0.0 pixel has the lowest
* value, and the rank = 1.0 pixel has the highest value.
* (3) We add mirrored boundary pixels to avoid boundary effects,
* and put the filter center at (0, 0).
* (4) This dispatches to grayscale erosion or dilation if the
* filter dimensions are odd and the rank is 0.0 or 1.0, rsp.
* (5) Returns a copy if both wf and hf are 1.
* (6) Uses row-major or column-major incremental updates to the
* histograms depending on whether hf > wf or hv <= wf, rsp.
*/
PIX *
pixRankFilterGray(PIX *pixs,
l_int32 wf,
l_int32 hf,
l_float32 rank)
{
l_int32 w, h, d, i, j, k, m, n, rankloc, wplt, wpld, val, sum;
l_int32 *histo, *histo16;
l_uint32 *datat, *linet, *datad, *lined;
PIX *pixt, *pixd;
PROCNAME("pixRankFilterGray");
if (!pixs)
return (PIX *)ERROR_PTR("pixs not defined", procName, NULL);
if (pixGetColormap(pixs) != NULL)
return (PIX *)ERROR_PTR("pixs has colormap", procName, NULL);
pixGetDimensions(pixs, &w, &h, &d);
if (d != 8)
return (PIX *)ERROR_PTR("pixs not 8 bpp", procName, NULL);
if (wf < 1 || hf < 1)
return (PIX *)ERROR_PTR("wf < 1 || hf < 1", procName, NULL);
if (rank < 0.0 || rank > 1.0)
return (PIX *)ERROR_PTR("rank must be in [0.0, 1.0]", procName, NULL);
if (wf == 1 && hf == 1) /* no-op */
return pixCopy(NULL, pixs);
/* For rank = 0.0, this is a grayscale erosion, and for rank = 1.0,
* a dilation. Grayscale morphology operations are implemented
* for filters of odd dimension, so we dispatch to grayscale
* morphology if both wf and hf are odd. Otherwise, we
* slightly adjust the rank (to get the correct behavior) and
* use the slower rank filter here. */
if (wf % 2 && hf % 2) {
if (rank == 0.0)
return pixErodeGray(pixs, wf, hf);
else if (rank == 1.0)
return pixDilateGray(pixs, wf, hf);
}
if (rank == 0.0) rank = 0.0001;
if (rank == 1.0) rank = 0.9999;
/* Add wf/2 to each side, and hf/2 to top and bottom of the
* image, mirroring for accuracy and to avoid special-casing
* the boundary. */
if ((pixt = pixAddMirroredBorder(pixs, wf / 2, wf / 2, hf / 2, hf / 2))
== NULL)
return (PIX *)ERROR_PTR("pixt not made", procName, NULL);
/* Set up the two histogram arrays. */
histo = (l_int32 *)CALLOC(256, sizeof(l_int32));
histo16 = (l_int32 *)CALLOC(16, sizeof(l_int32));
rankloc = (l_int32)(rank * wf * hf);
/* Place the filter center at (0, 0). This is just a
* convenient location, because it allows us to perform
* the rank filter over x:(0 ... w - 1) and y:(0 ... h - 1). */
pixd = pixCreateTemplate(pixs);
datat = pixGetData(pixt);
wplt = pixGetWpl(pixt);
datad = pixGetData(pixd);
wpld = pixGetWpl(pixd);
/* If hf > wf, it's more efficient to use row-major scanning.
* Otherwise, traverse the image in use column-major order. */
if (hf > wf) {
for (j = 0; j < w; j++) { /* row-major */
/* Start each column with clean histogram arrays. */
for (n = 0; n < 256; n++)
histo[n] = 0;
for (n = 0; n < 16; n++)
histo16[n] = 0;
for (i = 0; i < h; i++) { /* fast scan on columns */
/* Update the histos for the new location */
lined = datad + i * wpld;
if (i == 0) { /* do full histo */
for (k = 0; k < hf; k++) {
linet = datat + (i + k) * wplt;
for (m = 0; m < wf; m++) {
val = GET_DATA_BYTE(linet, j + m);
histo[val]++;
histo16[val >> 4]++;
}
}
} else { /* incremental update */
linet = datat + (i - 1) * wplt;
for (m = 0; m < wf; m++) { /* remove top line */
val = GET_DATA_BYTE(linet, j + m);
histo[val]--;
histo16[val >> 4]--;
}
linet = datat + (i + hf - 1) * wplt;
for (m = 0; m < wf; m++) { /* add bottom line */
val = GET_DATA_BYTE(linet, j + m);
histo[val]++;
histo16[val >> 4]++;
}
}
/* Find the rank value */
sum = 0;
for (n = 0; n < 16; n++) { /* search over coarse histo */
sum += histo16[n];
if (sum > rankloc) {
sum -= histo16[n];
break;
}
}
k = 16 * n; /* starting value in fine histo */
for (m = 0; m < 16; m++) {
sum += histo[k];
if (sum > rankloc) {
SET_DATA_BYTE(lined, j, k);
break;
}
k++;
}
}
}
} else { /* wf >= hf */
