On Wed, Oct 09, 2013 at 08:16:41PM -0400, Matthew Hunt wrote:
> To show the effects of pixel fill factor on aliasing, I coded up a
> small simulation. This 1000x1000 starting image:
I don't speak python, but to have an output array of the same size, would I
want something like:
def DownsampleImage(image, kernel):
out = np.zeros([math.floor(image.shape[0] / 9.0), math.floor(image.shape[1]
/ 9.0)])
outbig = np.zeros([math.floor(image.shape[0]), math.floor(image.shape[1])])
for x in range(out.shape[0]):
for y in range(out.shape[1]):
superpixel = image[x*9:x*9+9, y*9:y*9+9]
product = superpixel * kernel
value = np.sum(product)
out[x,y] = value
for x9 in range(0,9):
for y9 in range(0,9):
outbig[x*9+x9,y*9+y9]=value
return outbig
>
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/micro-auto-focus-test-2.png
> (from http://www.komar.org/faq/camera/auto-focus-test/ )
>
> represents the image falling onto a 111x111 monochromatic pixel
> sensor. Since each sensor pixel sees 9x9 pixels of the original image,
> we can create 9x9 downsampling kernels to simulate various sensor
> pixel fill factors.
>
> Here is the resulting image from a kernel using only a 1x1 portion of
> the 9x9 kernel (1% fill factor, approximating "instantaneous" or
> infinitesimal point sampling):
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/kernel_1.png
>
> A 3x3 kernel (11% fill factor):
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/kernel_3.png
>
> A 5x5 kernel (31% fill factor):
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/kernel_5.png
>
> A 7x7 kernel (61% fill factor):
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/kernel_7.png
>
> A 9x9 kernel (100% fill factor--no insensitive gap between pixels):
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/kernel_9.png
>
> And finally the code:
> https://dl.dropboxusercontent.com/u/20239870/Aliasing/FillFactor.py
>
> You can see that the sensor pixel fill factor has a considerable
> effect on the amount of aliasing in the output image.
>
> On Wed, Oct 9, 2013 at 12:08 PM, Larry Colen <[email protected]> wrote:
> > It seems to me that if you had a rear illuminated sensor, with no space
> > between the pixels, and it had no bayer filter, then aliasing/moire would
> > not happen, because the light value would be averaged over the whole sample.
> >
> > It's the discontinuous aspect of what is effectively three overlayed photos
> > that is causing the aliasing.
> >
> > Is this correct?
> >
> > --
> > Larry Colen [email protected] http://red4est.com/lrc
> >
> >
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