Raw histogram and why does it matter

Ok im going to give it away now only because i just went into the studio and shot my Hand in my normal position for head shots and then run it through bobs program and my midtones are PERFECT Im the man 😎😎😎
do me a favor and shoot the palm of you hand in any auto exposure mode ,view it in bobs program and it should have the EV0 perfectly in the middle of you readings , hope that makes sense. you dont win a lolly pop 😁

No problem, just do what works best for you.

To maximise the quality of my raw data I don't need any surface as I described earlier.

agree but its a good exercise just the same. am i going to use it in the future , cant think of any reason so far over my normal procedure, but you never say never. and its been a great discussion to push the boundaries anyway and play with a new software program that ive been hearing about for 10 years and whether the topic went off the rails or not it doesn't really matter.😎

I did that exercise years ago when I started out shooting sooc jpegs until I started shooting raw and realised I don't need any surface to maximise the quality of my raw data as described earlier.

My experience has been that I'm usually happier and more productive if I can resist prejudging or generalizing much with regard to individuals or groups based on their occupation or other categories with which they may be associated.

Not the same image, but still dark one.

No problem. The point I am making is that if I have choice whether to ask a camera manufacturer's marketing person or their engineer about anything relating to how a camera works or about any of the technical aspects of photography I will always ask the engineer.

Of course if a marketing person is the only choice I would still ask but I would have less confidence in the accuracy of their information.

I wonder about the definition. RAW is just a file extension. You can hide a lot under it. If it is just less bit depth file, it is still close to RAW file format. And therefore even engineers might be more likely call it a RAW. Definitions can and DO change, and new are added, if we need to be more specific.

I don't know because I've always directed technical inquiries to the tech support department rather than marketing or engineering.

I have worked for and with a broad assortment of people in marketing positions to supply the images they need of their products. It's generally been a pleasure to do so. Where product images are being generated by an in-house studio, the photographers and studio will generally be part of the marketing department.

it can measure DR

It's a good point to raise. Raw image formats are essentially unprocessed (or minimally processed) files containing the raw capture data needed to process and edit a file for the display or printing of a visible finished image.

The great thing about raw files, compared to film or processed image formats, is that the capture data can be processed and edited any number of times in different ways for different purposes. That said, when you import an image into a conventional raw editing program; a number of basic processing steps have occurred in the background before you see it.

Here's a black frame from a Panasonic S1:

Which shows similar weird "anti-coring" around black. I posted this - or a very similar image - on DPReview a while ago. There was some thought that the notch was caused by some kind of rounding error, but I have trouble imagining a mechanism.

Another weird thing is the exp(-abs(x)) distribution in the flanks.

I tried looking at the red channel with the central half-dozen levels stretched from black to white, and looking at a real FFT of the same thing, but couldn't see anything obvious.

I wondered if something was going wrong at the level of the ADCs.

Were there some way of fixing the "anti-coring", the noise would look quite good.

A (Read-noise * gain + conversion-noise) model doesn't work here, or for CrashpcCZ's camera.

Thanks. The log scale makes it clearer that the "anti-coring" notch doesn't go all the way dowm, in any channel, for any of the values close to black.

The rest of the distribution is a bit different to what I get on Panasonic S1 - your noise distribution is less symmetric, with a bit of a tail at the high end.

I don't know what that means.

I have no other explanation that the noise is not random. There can be many underlying reasons for that.

Anyways I have neither reason nor tools to diagnose and do anything with such output. 😅

I never even saw it.

That's what I said, yes. That's what Sony said in their definition. And here is what Nikon wrote: "Exclusive to Nikon cameras, the NEF is Nikon's RAW file format. RAW image files, sometimes referred to as digital negatives, contain all the image information captured by the camera's sensor, along with the image's metadata (the camera's identification and its settings, the lens used and other information). The NEF file is written to the memory card in either an uncompressed or "lossless" compressed form. " -- www.nikonusa.com/en/learn-and-explore/a/products-and-innovation/nikon-electronic-format-nef.html

RawDigger opens lossy compressed pseudo-raw files to help researches analyze the differences.
Ciao.

Yes, I wouldn't get too gung-ho about declaring raws as non-images, either. Why reach for the binary definitions, when nuance does a much better job?

I like to think in terms of what happens when we stretch the parameters. For example, if a monitor had enough resolution or you stood far enough away from it, you could actually see the CFA pattern go extinct, whether your display is monochrome or color. So as far as CFA is concerned, it may only be an issue when we are magnifying the pattern too much, just like when we look at a printed image or a monitor screen under a microscope, and see dither patterns or separate little red, green, and blue rectangles; it is just a matter of degree. You could drop 2 out of 3 color channels just like a CFA in each pixel in a quality, realistic sRGB image, and if you step back far enough, the CFA pattern will disappear, and the image will simply seem a little too green and a bit too dark, but varying the brightness of pixels could get around that, and there are many monitors now that can give high pixel output, to compensate.

We could throw a convolution of

0.25 0.25 0.00
0.25 0.25 0.00
0.00 0.00 0.00

on your image, and the CFA effect vanishes, or just swap neighbor pixels randomly, and you get a noise dither instead of a CFA.

Perhaps it would be better to ask how realistic an "alleged" image is, than to ask if it is really an image.