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08-05-2015, 05:25 AM   #1
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JPEG Recorded Pixels - benefits of turning it down?

OK, so in the K5 menu under "JPEG recorded pixels", I have the option of 16MP, 10MP, 6MP and 2MP.

Because my use of the camera at work involves medical and forensic imaging, I keep it at 16MP most of the time (I shoot hi-res jpg because it's easier when e-mailing images for rapid consultation, and for reasons of accountability I don't want to be seen to be doing any post-processing when doing coronial work).

However, the options are there - and so I'm coming to ask the obvious question. Apart from the smaller file size being an advantage when memory is at a premium, and possibly allowing more shots into the buffer on burst mode, what (if any) are the benefits of turning down the megapixels? I have frequently considered turning it down to six, seeing as that was what I was getting out of my *ist-DL, and for the most part this was quite adequate for personal use.

08-05-2015, 05:36 AM   #2
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I use 10MP ** + RAW
08-05-2015, 05:54 AM   #3
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@pathdoc, you already covered the benefits: smaller files and longer bursts. You sacrifice detail.

In your line of work 6mp might be a good solution. For general photography I always use maximum resolution for cropping flexibility.
08-05-2015, 07:31 AM   #4
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What size are you/they viewing the images at? If they are looking at it on a tablet for example then no one is using the 16mp. If they are looking at it on a big hi-res monitor then maybe. Are you zooming in to 1:1 or just viewing at screen size? If 1:1 then I would keep the 16mp. If just at screen size then figure the biggest screen size and that is all that is really being used.

Also, consider future uses. Will those images ever be used later, perhaps on higher resolution equipment? Or are they one time use and not looked at again?

Just some things to consider.

08-05-2015, 08:01 AM   #5
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I almost always use 16MP for everything - the question is whether there are any benefits from choosing anything else. Among other things, what is the sensor/processor combination actually DOING when I choose a lower resolution? If it's merging pixels somehow, does this suggest the possibility of better signal/noise ratios at higher ISO/in lower light?
08-05-2015, 09:42 AM   #6
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Yes, downsampling reduces both resolution and noise.
08-05-2015, 10:09 AM   #7
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Excellent - I suppose the next question to ask is which drops faster, and where is the cutoff beyond which the gains are outweighed by the losses? I suspect some experiments in this regard are called for, starting at very high ISO and working down. I for one am very impressed with how an f/1.8 lens on my K5, overexposed five stops at ISO 51,200, is able to turn night into day in my backyard. I'd be prepared to lose some resolution if I could cut down the noise a bit.
08-05-2015, 12:26 PM   #8
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QuoteOriginally posted by pathdoc Quote
I'd be prepared to lose some resolution if I could cut down the noise a bit.
Interesting idea.
So I tried it approximately on my old Olympus which is noisy in low light by today's standards.
The camera was set to record the raw 3000 x4000 plus a low resolution 1200 by 1600 jpg

Here is the noisy raw (as tiff) increased in brightness
https://app.box.com/s/vdtet657ampi0qjiwdzps4bf22xjkgor
Here is the low res jpg, increased in brightness
https://app.box.com/s/qn64e4zpo9qpc64r46jupjxrs3i2f0vm

Undersampling reduces noise because it has to be followed by a low pass filter ( which may be the monitor itelf).

When an image is downsampled digitally before its resolution is limited, aliasing will occur.
I read that We don't always object to some aliasing due to the way the eyes work.
(compared to the ears listening to music with aliasing for example, which is objectionable.)

The bottom line is:
A photo is irreversible, so entropy must increase in any processing of it. That means a degradation of fidelity compared to the original sensor image, when any post processing is done.

Ref: John B Williams" Image Clarity" Chapter 5 gives a nice explanation with diagrams of Theory of Image Degradation, in terms of entropy and the degradation equation.
The composite spread function is sum-in-quadrature of the spread functions of each degradation. In my example the dominant spread function was by the undersampling.

There are probably more advanced ways to reduce the noise while minimizing the spread function, other than a crude undersampling.

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