Thanks for answering Aivar,
I think what your reply did for me is to have me take a step back and
consider what we're modeling. If you look at my replies below, I think
that the best solution is to use a model where the background is white
and each successive layer filters out some of that background, like a
gel. A layer attenuates the underlying layer by a fraction of (1 -
alpha/255 * (1 - red/255)), resulting in no attenuation for 255 and
attenuation of alpha/255 for zero. We can then use a red converter
that returns a value of 255 for the blue and green channels and the
model and math work correctly.
On Mon, Jul 15, 2013 at 1:59 PM, Aivar Grislis <[email protected]
<mailto:[email protected]>> wrote:
I have an ImgPlus backed by an RGB PlanarImg of UnsignedByteType
and ARGBType.alpha(value) is 255 for all of them, so aSum is 765.
It would appear that the correct solution would be to divide aSum
by 3.
Isn't it unusual to define an alpha for each color component,
generally you have a single A associated with a combined RGB? So
averaging the three alphas might make sense here, because I think
they should all be the same value.
I think you're right, the model always is that each pixel has an alpha
value that applies to R, G and B. The image I was using was the Clown
example image. DefaultDatasetView.initializeView constructs three
RealLUTConverters for the projector, one for red, one for green and
one for blue which sends you down this rabbit hole.
In addition, there's no scaling of the individual red, green and
blue values by their channel's alpha. If the input were two
index-color images, each of which had different alphas, the code
should multiply the r, g and b values by the alphas before
summing and then divide by the total alpha in the end. The alpha
in this case *should* be the sum of alphas divided by the number
of channels.
I think alpha processing is more cumulative, done layer by layer
in some defined layer order. For a given pixel say the current
output pixel value is ARGB1 and you are compositing a second image
with value ARGB2 on top of it: For the red channel the output
color should be ((255 - alpha(ARGB2)) * red(ARGB1) + alpha(ARGB2)
* red(ARGB2)) / 255. The alpha of ARGB1 is not involved.
I think that's a valid interpretation. I've always used (alpha(ARGB1)
* red(ARGB1) + alpha(ARGB2) * red(ARGB2)) / (alpha(ARGB1) +
alpha(ARGB2)) because I assumed the alpha indicated the
strength of the blending of each source. In any case, the code as it
stands doesn't do either of these.
In other words, if you add a layer that is completely opaque you
no longer have to consider any of the colors or alpha values
underneath it.
I think the bigger issue here is this code is specifically
designed to composite red, green and blue image layers. It's a
special case since for a given pixel the red comes from the red
layer, blue from blue layer, and green from green layer. These
layers shouldn't be completely opaque, since the colors wouldn't
combine at all then or completely transparent since then they
wouldn't contribute any color. I don't think transparency is
useful here.
So this is an argument for blending instead of layering - transparency
would be useful if the images were blended and treated as if on a par
with each other, allowing the user to emphasize one channel or the other.
It's also possible that a multichannel image with > 3 channels is
being displayed with more color channels, namely cyan, magenta,
and yellow. The code here is designed to stop overflow, but I'm
not convinced those extended color channels would combine
meaningfully.
Aivar
In addition, there's no scaling of the individual red, green and
blue values by their channel's alpha. If the input were two
index-color images, each of which had different alphas, the code
should multiply the r, g and b values by the alphas before
summing and then divide by the total alpha in the end. The alpha
in this case *should* be the sum of alphas divided by the number
of channels.
I think alpha processing is cumulative layer by layer.
This brings up some interesting questions:
1) If the first, bottom-most layer is transparent, what color
should show through? Black, white? Or perhaps it's best to
ignore this base layer transparency.
Maybe the model should be that the background is white and successive
layers are like gel filters on top. In that case, you'd have:
red = (255 - alpha(ARGB2) *(255 - red(ARGB2))/255) * red(ARGB1)
And maybe that points to what the true solution is. For the default,
we could change things so that red channel would have blue = 255 and
green = 255 and the first composition would change only the red channel.
2) If you wanted to composite several transparent images, how do
you calculate the transparency of the composite? I'm not sure
this is something we need to do.
Aivar
On 7/15/13 10:31 AM, Lee Kamentsky wrote:
Hi all,
I'm looking at the code for
net.imglib2.display.CompositeXYProjector and as I step through
it, it's clear that the alpha calculation isn't being handled
correctly. Here's the code as it stands now, line 190 roughly:
for ( int i = 0; i < size; i++ )
{
sourceRandomAccess.setPosition( currentPositions[ i ], dimIndex );
currentConverters[ i ].convert( sourceRandomAccess.get(), bi );
// accumulate converted result
final int value = bi.get();
final int a = ARGBType.alpha( value );
final int r = ARGBType.red( value );
final int g = ARGBType.green( value );
final int b = ARGBType.blue( value );
aSum += a;
rSum += r;
gSum += g;
bSum += b;
}
if ( aSum > 255 )
aSum = 255;
if ( rSum > 255 )
rSum = 255;
if ( gSum > 255 )
gSum = 255;
if ( bSum > 255 )
bSum = 255;
targetCursor.get().set( ARGBType.rgba( rSum, gSum, bSum, aSum ) );
I have an ImgPlus backed by an RGB PlanarImg of UnsignedByteType
and ARGBType.alpha(value) is 255 for all of them, so aSum is 765.
It would appear that the correct solution would be to divide aSum
by 3. In addition, there's no scaling of the individual red,
green and blue values by their channel's alpha. If the input were
two index-color images, each of which had different alphas, the
code should multiply the r, g and b values by the alphas before
summing and then divide by the total alpha in the end. The alpha
in this case *should* be the sum of alphas divided by the number
of channels.
However, I think the problem is deeper than that. For an RGB
ImgPlus, there are three LUTs and each of them has an alpha of
255, but that alpha only applies to one of the colors in the LUT.
When you're compositing images and weighing them equally, if two
are black and one is white, then the result is 1/3 of the white
intensity - if you translate that to red, green and blue images,
the resulting intensity will be 1/3 of that desired. This might
sound weird, but the only solution that works out mathematically
is for the defaultLUTs in the DefaultDatasetView to use color
tables that return values that are 3x those of ColorTables.RED,
GREEN and BLUE. Thinking about it, I'm afraid this *is* the
correct model and each channel really is 3x brighter than possible.
It took me quite a bit of back and forth to come up with the
above... I hope you all understand what I'm saying and understand
the problem and counter-intuitive solution and have the patience
to follow it. Dscho, if you made it this far - you're the
mathematician, what's your take?
--Lee
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