lsst.afw g1b7e58284d+42a83f9714
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(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
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:
(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:
(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)
The xy_loc::cached_location_t
variables remember relative positions.
We can rewrite this to move setting nw
, se
etc. out of the loop:
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/=
N.b. you can use the iterator embedded in the locator directly if you really want to, e.g.
we called the iterator xy_x_iterator
, not x_iterator
, for consistency with MaskedImage.
Finally write some output files and close out main()
: