[Image-SIG] Two PIL based Hill Shading Implementations, using Python & Python/C.
jb at langarson.com.au
Thu Feb 8 12:49:44 CET 2007
It's good to see an example (albeit partial) like this, I haven't
really used ImageMath and ImageFilter. Would be interesting to compare
with equivalent numpy implementations performance-wise for some image
Douglas Bagnall wrote:
> John Barratt wrote:
> This is an observation, not a recommendation, but you could *almost* do
> all of this in pure PIL, without explicit loops. You could find the
> slope like so:
> dxfilter = ImageFilter((3,3), [1, 0, -1,
> 2, 0, -2,
> 1, 0, -1], 1)
> dyfilter = ImageFilter((3,3), [-1, -2, -1,
> 0, 0, 0,
> 1, 2, 1], 1)
> im_dx = img.filter(dxfilter)
> im_dy = img.filter(dyfilter)
> im_slope = ImageMath.eval("(a*a + b*b) ** 0.5)", a=im_dx, b=im_dy)
> The simple trig functions could use Image.point:
> def _sin(x):
> return 128 + sin(x) *127 #scaled to save precision
> im_sin_slope = im_slope.point(_sin)
> which should be quicker (though less accurate) than other methods,
> because it builds a lookup table rather than calculating each point.
> The tricky one looks to be the atan2 used to calculate the aspect.
> Either it needs to be split into two functions, one calculating
> atan(dy/dx), and the other calculating the correct quadrant, or it needs
> to be approximated using arithmetic in ImageMath.
> After that it is just a matter of back-scaling, multiplying and summing,
> which ImageMath.eval and other functions can do.
> but, as I said, I don't recommend it.
John Barratt - www.langarson.com.au
Python, Zope, GIS, Weather
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