Re: OT: 16 bit editing myth or reality?
You are absolutely right, my "simulation" is rather simplistic and of course
someone else probably did a much more in depth study of this subject before
me. I just wanted to put numbers on the popular advice of working in 16 bit
mode, mostly for myself but then I thought it might be useful to others.
I would add to what is said below by both of us, all of this as to be put in
perspective because of our ability to discrimitate between levels as been
estimated at about 1%, this less then 1 in 7 bits (2^7 = 128). Before we
disagree on this, I'll add that at this time, color science asn't come up
with a truly perceptually uniform color model to represent the human vision.
This 1% value is valid only in a specific context and most probably not
applicable in real world situation.
----- Original Message -----
From: "Ryuji Suzuki" <firstname.lastname@example.org>
Sent: Friday, December 14, 2007 12:35 PM
Subject: Re: OT: 16 bit editing myth or reality?
> Although I don't disagree with your conclusion, I also
> recognize the same limitations as what you noted.
> This is actually a class of problems for which an effective approach
> already exists in statistical literature. I don't know if
> there is any real statistician, probability theorist or
> information theorist on this list, but I just summarize it
> below. IF not interested, please skip to the next message.
> Your analysis used only simple curves and not manipulations
> that require multiple pixels, such as sharpening, unsharp
> mask, blur, resize, etc. Therefore, without loss of
> generality, you can consider a single pixel case. (The analysis
> can be expanded to incorporate dependency where necessary.)
> The study system can be viewed as follows:
> X --> quantization1 --> manipulation --> quantization2 --> Y
> Let X be a random variable with a probability distribution of
> an image. Naturally, Y is another random
> variable. Quantization 1 is either 8 or 16 bits. Quantization
> 2 is always 8 bits.
> The question is how much information Y posses about X, and how
> much of it is lost by applying 8-bit or 16-bit quantization in
> the quantization 1. The ultimate question is what is the
> difference in the two and whether it is significant in practice.
> Now we can use Fisher information of Y about X as the
> information measure, while quantization 1 and quantization 2
> both represent communication channels wherein Shannon
> information capacity is limited. This is exactly the kind of
> problems tackled in the field of "information geometry"
> pioneered by Shun-ichi Amari.
> Ryuji Suzuki
> "I wonder how many research workers there are in various fields all
> over the world, who are at this time struggling with problems whose
> solutions already exist in the statistical literature." (Mark Kac 1975)
> From: Yves Gauvreau <email@example.com>
> Subject: OT: 16 bit editing myth or reality?
> Date: Fri, 14 Dec 2007 11:39:17 -0500
> > Hi,
> > I was curious to verify that editing in 16 bit mode (16/48) was really a
> > plus or a myth especially when considering a printed image.
> > So I generated a large number (1 million) of normally distributed real
> > numbers (doubles) in the range of [0..1]. If you made an histogram of
> > numbers it would look pretty much like what you would observe with a
> > image. I can add that this data set is similar to a black and white
> > I then converted these real numbers to a set of 8 bit integers [0..255]
> > also to a set of 16 bit integers [0..65535] thus creating 2 sets of
> > from the same original set of real numbers.
> > I then applied 5 different curves to each set of values. The simple
> > was y = x^1/g where x is the set of either the 8 or 16 bit integers, y
> > the resulting set of new values and g was either 1.5, 1.8, 2.0, 2.2,
> > These curves represent a mild to heavy raise of a single control point
> > input 50. All this created 5 sets of new values for both the 8 and 16
> > sets or 10 new sets if you prefer.
> > I then counted the unique levels of the original 8 bit integer set and
> > bit integer set that was converted to 8 bits assuming this would happen
> > we printed our 16 bit original file.
> > Next I counted the unique discrete levels present in each of the 10 data
> > sets. Don't worry the software I used for this counted them for me. This
> > counting would be similar to counting the bins of an histogram having a
> > count of 1 or more in them. In simpler terms, I was interested to find
> > the number of levels we loose by applying a curve to an image, this
> > look like holes on an histogram.
> > Here are the results:
> > The 8 bit integer set as 238 out of the possible 256 levels
> > curve 1 => 203 or 85.3% (203/238)
> > curve 2 => 188 or 79.0%
> > curve 3 => 178 or 74.8%
> > curve 4 => 170 or 71.4%
> > curve 5 => 159 or 66.8%
> > The 16 bit integer set as also 238 out of the possible 256 levels when
> > converted back to 8 bits
> > curve 1 => 216 or 90.8%
> > curve 2 => 203 or 85.3%
> > curve 3 => 192 or 80.7%
> > curve 4 => 185 or 77.7%
> > curve 5 => 173 or 72.7%
> > Conclusion:
> > Though I started with random numbers which mean the data is not a real
> > image, I took great care to use numbers that would be representative of
> > real world B&W image. Also the curve I use may not be representative of
> > actual transformation one would use on a real image but it is actually
> > inverse gamma transformation and this type of transform is used
> > all the time in color managed environment. I think we can say that both
> > data and the curve are representative of actual editing that could be
> > on real world images though this particular data set is similar to a B&W
> > image and it may not be the same with a color image.
> > I think we can safely say that this particular editing simulation shows
> > we would benefit from working in 16 bit mode.
> > But I remind you that other types of editing may or may not allow us to
> > to the same conclusion.
> > Hope this was helpful,
> > Regards,
> > Yves