# How to count EFFECTIVE number of pixels in a photo

Started 5 months ago | Questions thread
Re: How to count EFFECTIVE number of pixels in a photo

ProfHankD wrote:

il_alexk wrote:

Just trying to understand if I really need 44Mp sensor, PP in Lightroom started to take way too long with their latest AI denoising.

So you want to do the denoising AFTER resizing? Well, that's a lot harder. Basically, recognizing noise as noise to confirm that a certain level of resizing will not cost real detail is virtually identical complexity to recognizing noise to eliminate it.

No, no, no. Here is my thoughts process. 😂

My 44Mp images at ISO6400 obviously lose details compared to, say, ISO 100. Plus I lose more details after denoising. So how many meaningful pixels is effectively left? Wouldn't it be great to have a research paper that studies effective image resolution vs ISO?

So I am considering to downgrade to A7III with 24Mp pixels, which both would reduce the PP time and improve the AF. Just want to make sure I get enough resolution for 50-30% cropping. Low ISO isn't a brainer, A7R3 is unbeatable, however at ISO 4000-6000 where most of my photos are things are less than trivial and A73 might be equally good.

You certainly could switch to a different camera, but simply downscaling A7RIII images to 24MP should produce very similar results.

I thought about it. Still would like an objective tool to tell me how much details I lose .

So, how would you "make one"?

As described above... Easy, but researchy.

This is what it said:

Here's a step-by-step approach:

1. Calculate the entropy of the original image.
2. Calculate the entropy of the denoised image.
3. Compare the two entropies to determine the percentage of detail retained.
4. Use this percentage to determine the effective resolution.

Can't get my brain around this, I can think about corner cases that will brake this logic, but maybe I'm wrong and should go for it. 😂

I might try asking it to write a python or Octave scripts based on this idea for me.

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Cheers,
Alex

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