(Return to Images)
Iterators provide access to an image, pixel by pixel. You often want access to neighbouring pixels (e.g. computing a gradient, or smoothing). Let's consider the problem of smoothing with a
kernel (the code's in image2.cc):
Start by including Image.h defining a namespace for clarity:
Declare an Image
Set the image to a ramp
for (
int y = 0;
y != in.getHeight(); ++
y) {
for (ImageT::xy_locator
ptr = in.xy_at(0,
y),
end = in.xy_at(in.getWidth(),
y);
ptr !=
end;
}
}
That didn't gain us much, did it? The code's a little messier than using x_iterator. But now we can add code to calculate the smoothed image. First make an output image, and copy the input pixels:
ImageT out(in.getDimensions());
out.assign(in);
(we didn't need to copy all of them, just the ones around the edge that we won't smooth, but this is an easy way to do it).
Now do the smoothing:
for (
int y = 1;
y != in.getHeight() - 1; ++
y) {
for (ImageT::xy_locator
ptr = in.xy_at(1,
y),
end = in.xy_at(in.getWidth() - 1,
y),
*optr =
ptr(-1, -1) + 2 *
ptr(0, -1) +
ptr(1, -1) + 2 *
ptr(-1, 0) + 4 *
ptr(0, 0) +
}
}
(N.b. you don't really want to do this; not only is this kernel separable into 1 2 1 in first the x then the y directions, but lsst::afw::math can do convolutions for you).
Here's a faster way to do the same thing (the use of an Image::Ptr is just for variety)
out2->assign(in);
typedef ImageT::const_xy_locator xy_loc;
for (
int y = 1;
y != in.getHeight() - 1; ++
y) {
xy_loc
dot = in.xy_at(1,
y),
end = in.xy_at(in.getWidth() - 1,
y);
xy_loc::cached_location_t nw =
dot.cache_location(-1, -1);
xy_loc::cached_location_t n =
dot.cache_location(0, -1);
xy_loc::cached_location_t ne =
dot.cache_location(1, -1);
xy_loc::cached_location_t
w =
dot.cache_location(-1, 0);
xy_loc::cached_location_t c =
dot.cache_location(0, 0);
xy_loc::cached_location_t e =
dot.cache_location(1, 0);
xy_loc::cached_location_t sw =
dot.cache_location(-1, 1);
xy_loc::cached_location_t s =
dot.cache_location(0, 1);
xy_loc::cached_location_t se =
dot.cache_location(1, 1);
for (ImageT::x_iterator optr = out2->row_begin(
y) + 1;
dot !=
end; ++
dot.x(), ++optr) {
}
}
The xy_loc::cached_location_t variables remember relative positions.
We can rewrite this to move setting nw, se etc. out of the loop:
xy_loc pix11 = in.xy_at(1, 1);
xy_loc::cached_location_t nw = pix11.cache_location(-1, -1);
xy_loc::cached_location_t n = pix11.cache_location(0, -1);
xy_loc::cached_location_t ne = pix11.cache_location(1, -1);
xy_loc::cached_location_t
w = pix11.cache_location(-1, 0);
xy_loc::cached_location_t c = pix11.cache_location(0, 0);
xy_loc::cached_location_t e = pix11.cache_location(1, 0);
xy_loc::cached_location_t sw = pix11.cache_location(-1, 1);
xy_loc::cached_location_t s = pix11.cache_location(0, 1);
xy_loc::cached_location_t se = pix11.cache_location(1, 1);
for (
int y = 1;
y != in.getHeight() - 1; ++
y) {
xy_loc
dot = in.xy_at(1,
y),
end = in.xy_at(in.getWidth() - 1,
y);
for (ImageT::x_iterator optr = out2->row_begin(
y) + 1;
dot !=
end; ++
dot.x(), ++optr) {
}
}
You may have noticed that that kernel isn't normalised. We could change the coefficients, but that'd slow things down for integer images (such as the one here); but we can normalise after the fact by making an Image that shares pixels with the central part of out2 and manipulating it via overloaded operator/=
{
ImageT center = ImageT(
*out2,
center /= 16;
}
N.b. you can use the iterator embedded in the locator directly if you really want to, e.g.
for (
int y = 0;
y != in.getHeight(); ++
y) {
for (ImageT::xy_x_iterator
ptr = in.xy_at(0,
y).x(),
end = in.xy_at(in.getWidth(),
y).x();
ptr !=
end;
}
}
we called the iterator xy_x_iterator, not x_iterator, for consistency with MaskedImage.
Finally write some output files and close out main():
out.writeFits("foo.fits");
out2->writeFits("foo2.fits");
return 0;
}
