Joofa

HperLogLog, for e.g.

You are welcome, Prof. Fossum. Your guidance was much appreciated in understanding the process. I look forward to the newer visualizations with the neural network work that you reported.

IMHO, it depends - for e.g., with QIS one could have a 'sliding window' of frame integration, that could potentially result in a larger DR, if the QIS frame capture rate is high enough vis-a-vis ...

Prof. Chan, Thanks for your comments. It is an interesting work. Your comments are useful and I went back to the paper and read portions of it again and can appreciate your work more now - I know I ...

It is welcoming to see applications of DNNs to data of QIS type. And, that opens up the field for camera manufactures if inference computation can be kept sufficient low power for making the ...

Ok, I guess you had a change of opinion. Good.

Isn’t that your job to figure out? You were making claims about potential sufficiency of single meaurements.

You don’t need my camera. You just need a single image, and it was provided to you. You should be able to download it.

Well, you are wiggling your way out of the situation you put yourself in. But it is OK as long as you understand what is being said here.

The quantum randomness here (shot noise) is different from measurement noise (read noise). And, that is the gist. In a more general setting, the overall notion of internal vs external noises has ...

The thing that is important in my mind is the equation, which I mentioned in the original post, ( https://www.dpreview.com/forums/post/64327430 ): output = signal + noise This equation has a ...

I have highlighted above what DCox wrote ( one still photograph ). Not multiple images. And, you had an objection to that. Let me say it again, one still natural image (unless it is a uniformly lit ...

Right, multiple images, and to me that is contrary to your thesis the 'the noise is defined and and it (the variance) adds to spatial noise.' That was the whole point. Unlike read noise, shot noise ...

Ok, if the noise is 'defined', then you should be able to measure it. Kindly report the shot noise number for the image below and how you derived it: What is the numerical value of shot noise in ...

Of course, approximation . The earlier discussion insisted on exact .

Because, a number of different (closely placed) photon number values could potentially generate the same number of photoelectrons, which are actually measured. Hence, you can only argue ...

The pixel doesn't measure an exact number of photons. The exact number of photons impinged on a pixel for even an exac t number of photoelectrons measured is an unknowable quantity. Described only ...

Not good, then. https://github.com/imagej/imagej1/blob/master/ij/plugin/FFT.java

Well, first you yourself asked about the Nyquist and are now questioning its mentioning. You should make up your mind what you really want. Here: Not really about pixels. You assume a lot, many ...

Based upon your responses here I don't even think you understand what is the notion of 'nyquist' here.