Are bigger pixels less noisy?

Started 4 months ago | Discussions thread
JahnG
OP JahnG Veteran Member • Posts: 3,328
Re: Noise reduction

J A C S wrote:

I know a bit about noise even though this is not in my main area of research.

First, it is good to know something about the statistical characteristics of the noise. Is it an additive, or not, etc.; then what is the distribution, the strength, and the auto-correlation, which also determines the spectrum. A typical example is to have white additive noise, which can describe, I guess, most of the read noise (but not the shot noise).

Without additional assumptions, you cannot remove noise, period. After all, I can take a perfect photo of a noisy gray patch, and all NR software will remove most of it but that would be actual signal.

Fortunately, most of our photos are not like that, but some parts could look close, like the sand on a beach, etc. Then one tries to guess what is noise and what is signal because signal is expected to be more orderly. Just applying a low-pass filter is not a great NR since white noise, for example, has uniform spectrum on average, and the medium and the low frequency noise remain - they look like grain. You kill fine detail and fine noise but you leave "coarse" noise.

Algorithms based on the assumption that the image is "orderly" (sparse is some basis) might be classified as compressed sensing in a wide sense (I include various optimizations here, TV included). They work when they do and fail when they fail; for example, TV kills patterns. AFAIK, there are other algorithms looking for edges for example (the old DXO Prime claimed that) but I do not know details.

The newest trend is machine learning (AI). It tries to match parts of the image with parts of images in the "training set" somehow. There are lot of parameters to adjust there, there is a lot of trial and error and little theoretical understanding but they "work". DXO Prime AI, for example, does wonders IMO. It works on RAW only. This is what separates photography from other applications - we have three channels while many of the traditional techniques assume one.

Thanks, so perhaps not to generally expect wonders.

Just looked at Topaz DeNoise comments, and some were not necessarily satisfied with the newest version(s)

Jahn

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