are you workin any scientistic kind? because i'm a little bit confused about some of your words..

I do not understand your question here.

no. are you talking about security cams without affection to good picture and with pre/postprocessing?

A camera can have a lot of dynamic range, but little bit depth.

I am not singling-out security cameras, although there are certainly some that have increased DR and an 8-bit depth.

However, there are plenty of other examples, too. For instance, many cameras give a choice of bit depths -- yet the DR remains the same regardless of the chosen bit depth. So, at the lowest bit-depth setting, the camera has its greatest dynamic range, but has it's lowest bit depth.

Dynamic range and bit depth are two independent properties.

"CAN"! - picturesensors giving linear data, means, to save and sample them accordingly, you need a "linear" system,

As I am sure you know, sensors give analog data, and that info can be mapped to digital values in ways other than "linear."

Regardless, given a linear mapping method, a camera can still have little dynamic range and a great bit depth. Take any early 16-bit camera and compare its capture DR to that of a current 16-bit camera -- the newer cameras will generally capture a greater dynamic range. So, the early cameras have little capture DR but great bit-depth.

its quite good described with the bitdepth. 1bit for 1ELV (>1bit) - theoretical meaning 14bit **is able** to sample/save nearly 14ELV of visual data accordingly without loss/artifacts. that doesnt mean, if theres a 14bit ad-converter, the source side (here: sensor) must deliver the full range.

I am not sure what the point is here, but the value associated with each incremental step in bit-depth in a linear system is not a universal constant. That value can (and often does) vary from system to system, camera to camera. That variation is a precise reflection of why DR and bit-depth are different.

lol. no. DualISO is changing the ampification per sensel-line. both different amplificated "pictures" are limited in their dynamicrange, one's losing data in the lowlights, the other loses values in full-well-sensor-area (highlights). they're kind of preprocessed.

Thanks for the explanation of Dual ISO, but I already understood the basics of how it works.

As I said, Dual ISO gives a phenomenal increase to the capture dynamic range, yet the bit depth doesn't change. That fact is absolutely true.

However, Dual ISO does not change the dynamic range of each pixel in the sensor (I never claimed that it does). In addition, with Dual ISO, one is sacrificing resolution and color depth along the vertical axis for the increase in capture DR. I would also guess that Dual ISO makes the images more vulnerable to aliasing/moire.

By the way, a few years ago Panavision was working on its "Dynamax" HDR sensor, which used extra pixel groups of differing exposures, somewhat similar to Dual ISO. "Dynamax" is now the name of Panavision's sensor division (don't know what became of the HDR sensor).

but you said "zillions of real life examples". fine.

As I said, there are countless examples in which dynamic range and bit-depth are independent. Dual ISO is only one.

The situation that I gave above of setting a camera to its lowest and highest bit depth while yielding the same DR is another case. There are many cameras that have such capability, hence there are many such examples of how bit-depth is independent from DR.

The above scenario of an older camera with 16-bit depth and low capture DR compared to the capture DR of today's 16-bit cameras is yet another case of how DR and bit-depth are independent. There are many old and new cameras to compare, thus there a numerous examples demonstrating the independence between DR and bit-depth.

We haven't even touched on the differing dynamic ranges of digital systems and digital displays that have identical bit depths.

Again, we need look no further than ML for another example in which capture DR is independent from bit-depth -- HDR video. With HDR video, the DR increases, yet the bit-depth remains unchanged. Of course, we are not increasing the actual dynamic range of the sensor, and we sacrifice longer shutter speeds and suffer motion artifacts in exchange for the DR increase.

These general examples (along with the specific ML examples) are fairly clear, so I don't see the need to site particular digital cameras/systems to prove the point. However, I will, if you like.

a switch with two s**t**ates has no dynamic range.

Two shades can have dynamic range.

how do you describe dynamicrange between on and off? you need a **"lowest" measurable value (not zero!)**

Who said that the lower shade is "off/zero?"

However, zero is a given in any system, so, you are right, it should be considered as a third shade.

[/b]. leads to at least three states (or you said: two shades). means: [three states] 0, 0.5 and 1. whats the dynamicrange of that? other example: 4 states (2bit): 0, 0.33, 0.66, 1 (=1/0.33).. (16384 states) 14bit -> 1:16383 -> ln(16383)/ln(2) = 13.99 ELV

There is no way to quantify the specific dynamic range of any of those systems, unless the noise level is known. On the other hand, it seems that these examples demonstrate how dynamic range can relatively remain the same while the bit depth is changed.

"color" is just an electromagnetic property. if you measure three separate frequencies by its amount (here: photons), you just measure the dynamicrange in finite frequencies.. (please dont talk about the simplifaction from graphic-cards-world)

Well, if you take color on the "photon" level at the subject, you are talking about infinite frequencies.

However, my statement to which you responded involved the fact that color depth and bit depth are two different properties, so we are primarily referring to digital imaging systems. For the sake of simplification, let's address RGB digital imaging systems, and disregard alpha channels, Bayer interpolations or any obscure digital color systems. Let's also stick to simple raw imaging and not involve compression, dithering or any other such modifications.

Color depth in digital systems is a result of two primary factors: resolution and bit-depth. Here is the basic mathematical relationship:

**Color Depth = (Resolution x Bit Depth)**^{3}So, a small increase in resolution can yield a huge increase in color depth. Of course, an increase in bit-depth also boosts the color depth.

That's pretty much it.