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#1
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Now that we have high resolution, why isn't "binning" a standard option?
RichA wrote:
The combining of pixels into superpixels prior to digitization. 4 pixels of 7um become one of 14um. Low light shooting becomes much easier as effective ISO is raised. Not every situation calls for 12 megapixels of resolution, but often situations call for low light capability. What's wrong with binning in PP? I don't see a real need for in camera. -- Digital Fake Book Free chord/lyric display software for Windows http://www.mike-warren.net/digitalfakebook -- Posted via a free Usenet account from http://www.teranews.com |
#2
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Now that we have high resolution, why isn't "binning" a standard option?
The combining of pixels into superpixels prior to digitization. 4
pixels of 7um become one of 14um. Low light shooting becomes much easier as effective ISO is raised. Not every situation calls for 12 megapixels of resolution, but often situations call for low light capability. |
#3
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Now that we have high resolution, why isn't "binning" a standard option?
Ο "RichA" έγραψε στο μήνυμα
ups.com... The combining of pixels into superpixels prior to digitization. 4 pixels of 7um become one of 14um. Low light shooting becomes much easier as effective ISO is raised. Not every situation calls for 12 megapixels of resolution, but often situations call for low light capability. Excellent question and i presume quite easy to implement at the sensor level. |
#4
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Now that we have high resolution, why isn't "binning" a standard option?
In article . com, RichA
writes The combining of pixels into superpixels prior to digitization. 4 pixels of 7um become one of 14um. Low light shooting becomes much easier as effective ISO is raised. Not every situation calls for 12 megapixels of resolution, but often situations call for low light capability. At the sensor level those 4 colour 7um pixels become one monochrome 14um pixel - and your image reduces to 3Mp. To do binning on a conventional Bayer array while retaining colour information means combining non-adjacent pixels. That means even more complex circuitry and tracking in an already dense pixel. That, in turn, means the signal losses may swamp any noise benefits. For example, any 4x4 array on a standard Bayer sensor has 4 red, 4 blue and 8 green pixels. Each colour pixel has pixels of the other colours between them, so adjacent pixels cannot be binned. However non-adjacent pixels could be combined to give 1 red & blue and 2 green superpixels in a 2x2 array, with each superpixel spanning a 3x3 area of the originals. So, if your original pixels are 7um then the superpixels are actually on a 21um in size, but on a 14um pitch. ie. the superpixels physically overlap. That may not be a bad thing, since spatial coherence between pixels is Foveon's main feature, but the resolution would be less than a conventional 3Mp sensor. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#5
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Now that we have high resolution, why isn't "binning" a standardoption?
Kennedy McEwen wrote:
RichA writes The combining of pixels into superpixels prior to digitization. 4 pixels of 7um become one of 14um. Low light shooting becomes much easier as effective ISO is raised. Not every situation calls for 12 megapixels of resolution, but often situations call for low light capability. At the sensor level those 4 colour 7um pixels become one monochrome 14um pixel - and your image reduces to 3Mp. To do binning on a conventional Bayer array while retaining colour information means combining non-adjacent pixels. That means even more complex circuitry and tracking in an already dense pixel. That, in turn, means the signal losses may swamp any noise benefits. For example, any 4x4 array on a standard Bayer sensor has 4 red, 4 blue and 8 green pixels. Each colour pixel has pixels of the other colours between them, so adjacent pixels cannot be binned. However non-adjacent pixels could be combined to give 1 red & blue and 2 green superpixels in a 2x2 array, with each superpixel spanning a 3x3 area of the originals. So, if your original pixels are 7um then the superpixels are actually on a 21um in size, but on a 14um pitch. ie. the superpixels physically overlap. That may not be a bad thing, since spatial coherence between pixels is Foveon's main feature, but the resolution would be less than a conventional 3Mp sensor. Is binning any better that downsampling? |
#6
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Now that we have high resolution, why isn't "binning" a standard option?
In article , Paul Furman
writes Is binning any better that downsampling? In principle, yes, since you only have one read operation and therefore one read noise contribution, with sqrt(n) photon signal to noise. The problem comes with whether that sqrt(n) can be achieved in practice without any signal losses or additional noise. Downsampling, in contrast, has n read noise contributions. -- Kennedy Yes, Socrates himself is particularly missed; A lovely little thinker, but a bugger when he's ****ed. Python Philosophers (replace 'nospam' with 'kennedym' when replying) |
#7
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Now that we have high resolution, why isn't "binning" a standard option?
At the sensor level those 4 colour 7um pixels become one monochrome 14um
pixel - and your image reduces to 3Mp. What would the sensitivity of that monochrome pixel be though? Would it be the mean average of the sensitivities of the four pixels? That's what I'm assuming. I'm just wondering how the difference between the density of the green pixel filtration (relatively minor) and the blue pixel filtration (around 3 stops) would change how the binning operates. You seem to know about these things. Will |
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