# Downsizing for reducing noise



## alaios (Sep 23, 2014)

Hi all,
I wanted to ask you what techniques do we have for redusing the size of an image as a way to reduce the overall noise. Which technique do you apply to your files and is somehow a way to associate image resolution reduction with the gain you earn in terms of image quality?

Regards
Alex


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## Jimmsp (Sep 25, 2014)

alaios said:


> Hi all,
> I wanted to ask you what techniques do we have for redusing the size of an image as a way to reduce the overall noise. Which technique do you apply to your files and is somehow a way to associate image resolution reduction with the gain you earn in terms of image quality?
> 
> Regards
> Alex


It far from obvious to me that reducing the size of an image will reduce noise. It is more likely that it will be increased.

Think of noise as a random set of bad pixels at some density in the original image. Call this density Nd. The number of noisy pixels is just equal to Nd times the area of the image.
If I reduce the size of the image, I will have fewer noise pixels, but the density will, at best, remain the same; ie, it will look just as noisy.
And depending on how the size reduction is done (eg, sampling and averaging neighboring pixels) you stand a good chance of actually increasing the Nd if there are multiple noise pixels within your sampling volume.

Bottom line - use the noise reduction capability that LR provides you before you downsize your photo.


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## Victoria Bampton (Sep 26, 2014)

It's true that resampling can blur some of the noise, but you also lose some of the fine detail in the image.  Lightroom's noise reduction now works so well, it's rarely needed these days.


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## alaios (Oct 9, 2014)

thanks guys. Are not though those two answers a bit contradictory? What are the techniques I have to use to reduce noise and how they do work? Which one is appropriate for different type of noise?
Any material to further read on?
Regards
A


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## Jimmsp (Oct 9, 2014)

alaios said:


> thanks guys. Are not though those two answers a bit contradictory? What are the techniques I have to use to reduce noise and how they do work? Which one is appropriate for different type of noise?
> Any material to further read on?
> Regards
> A


They might seem a bit contradictory, but not necessarily to me. Lets say you have in some area a noise pixel with some intensity; eg 10. If I down sample and end up with  2 noise pixels close to each other of intensity 5, I call that increased noise, Victoria would call that blurred.

As to techniques, you have lots at your disposal, some of which will cost you a little bit of money. Lightroom has a fairly good noise reduction capability. It is recognized to be able to reduce color noise very well. It removes luminescent noise fairly well for low to mid level amounts of noise, imo. I shoot a Canon 60D. For ISOs of less than 600 or so, LR does a very good job of reducing luma noise. However, for larger ISO's, I resort to packages like Topaz deNoise, and Noiseware. Both do excellent jobs on images with a lot of luma noise.

But I have found experimentally that some images actually get the best look when I use both software packages in series. This isn't too surprising, since each (as well as LR) uses different math algorithms to find and eliminate noise. Thus, what one misses, the other finds. I have even had a couple of 6400 ISO images where I have even used LR to "fine tune" the final image using the spot adjustment brush. Just use them to the point where you start losing detail, them move to another one. My standard way of proceeding is to apply LR color noise reduction, then a small amount of LR luma noise reduction before I move to Topaz or Noiseware.
You should try these packages; both have demo versions. You can use Topaz as a plugin to LR, and Noiseware as a plugin to Photoshop or PSE.


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## alaios (Oct 10, 2014)

Hi thanks.
What is luminant noise and which of two programs I should try to buy then? I just wonder what Topaz and Noiseware really do that lightroom does not.

Alex


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## Tony Jay (Oct 11, 2014)

Hi Alex.

Lets investigate noise:
There are several sources of noise in the typical image

*Shot noise* (or pseudorandom noise) - this sort of noise results from small variations in light striking different sensels where it should be the same such as a segment of sky with identical luminance.
*Read noise* - this noise is the product of the sensels, circuits, electronics and analog-to-digital conversion process that introduces variations where they should not be. This type of noise is especially prominent in severely underexposed images.
*Pattern noise* - this noise is a product of the electronic circuits that are found in the sensor and affect the overlying sensels due to the production of heat and also electromagnetic interference.
*Thermal noise* - as mentioned above heat changes the performance of sensels. The electronic circuits during normal operation heat up and affect adjacent sensels.
Overall environmental thermal conditions also contribute to noise. Some medium format backs actually have cooling built in to reduce the contribution of thermal noise. Long exposures, such as when shooting star trails at night, are well known for producing a lot a thermal noise and its cousin, pattern noise.

Most of the noise produced by the above mechanisms is luminance noise.
*Colour noise* is a function of demosaicing which occurs when a RAW image is rendered.

The key to understanding luminance noise is the concept of the signal-to-noise ratio.
Each sensor will have a baseline noise signature that is a product of all the different noise sources apart from the shot noise that is a function of the characteristics of light striking the individual sensors.
If an image, or part of an image, is underexposed then the signal-to-noise ratio is low and and the variations in apparent acquired luminance data are enhanced and the result is what we perceive as a noisy image.
If the signal-to-noise ratio is high then any variations due to the baseline noise signature become impossible to distinguish and we perceive an image like this to be free of noise (although it is still present).

So, the key to managing noise in an image is not to only think about it in the post-processing phase.
I manage noise by planning how I will shoot.
The general principle is the more light that strikes the sensor the better right up to the point of blowing the highlights.
One wants to push the histogram to the right to a point just shy of blown highlights.
This approach is termed ETTR or Expose-To-The-Right.
Obviously this shooting technique only applies to shooting RAW - it simply will not give you the results that you want if you are shooting JPEG in-camera.

This next point is also worth making:
Most modern late-model cameras have excellent noise signature characteristics.
Cameras using the latest sony sensors such as the Nikon D800 or the new Pentax 645D (just released) are practically ISOless in the sense that cranking up the ISO appears not to increase the apparent noise.
Digital cameras using sensors that are even five years old have nowhere near the same performance.

Lets look at noise reduction in post-processing:
The principle of luminance noise reduction is very simple in concept - fine detail is simply blurred or smeared.
For me, being heavy handed with noise reduction is simply unacceptable since my images rely on fine detail.

So the best way of approaching noise reduction is to view it as part of image sharpening. Many guru's refer to the noise reduction slider as the fifth sharpening slider. More on this shortly.
Another important concept is not try and deal with noise reduction and sharpening issues that are limited a small part of the image with global adjustments.
All images require a degree of global capture sharpening and many images a degree of global noise reduction.
Other than that try to deal with other issues on a regional basis.
I often use the masking slider to limit sharpening to the edges that require it especially in an image that has noise issues since sharpening an image globally will augment the noise.
The benefit of not sharpening all the noise in the image is that the amount of global noise reduction that is required is reduced and so important fine detail will be preserved.
The adjustment brush has the option of applying both sharpening and noise reduction to selected regions of an image.
I will sometimes use the adjustment brush to deal with noise in underexposed areas where there may not be a lot of important detail anyway so the loss of fine detail will not be significant.
In the same way I might enhance the sharpening of selected areas of an image that are well exposed to augment the detail there. Since the apparent noise in these areas is imperceptible the sharpening here does not impact negatively.

In summary, I would strongly suggest that before you go chasing after noise reduction plug-in's that you analyse and learn all that is required across your entire workflow from camera choice, shooting technique, and Lightroom itself to reduce the impact of noise and increase image quality.
The sharpening and noise reduction algorithms in Lightroom are so good that the utility of other noise reduction software has been reduced to edge-cases.
I don't deny that they work, but then, so does Lightroom.
In your case I don't think you have come close to challenging the abilities of Lightroom yet.

Tony Jay


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## alaios (Oct 11, 2014)

Hey Jay thanks a lot for the answer.
Is very hard to find these days so well explained answers. !Bravo!
I understand that lightroom should be enough if I am doing my job right and I should invest my time there (doing the job right)

Alex


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## Victoria Bampton (Oct 11, 2014)

Great job Tony!


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## Jimmsp (Oct 13, 2014)

Tony Jay said:


> Hi Alex.
> 
> Lets investigate noise:
> There are several sources of noise in the typical image
> ...



Hi Tony,
Thanks for the very good summary of noise, and the recommendation. Your summary very nicely points out why the noise we see is so complicated.
I agree that the OP should start with LR first and master that.

However, I don't believe that 3rd party packages should be written off quite so easily. It depends a lot on the camera and how he shoots.
I do know that when I shoot my Canon 60D above 1200 ISO, which I sometimes do a lot for indoor sports and high action grandchildren, Lightroom does ok, but I generally need tools like Topaz deNoise or Noiseware if I am going to print any of these shots above 4x6 in size. And I have found that different shots at high ISO often benefit from a combination of noise reduction packages, including Lightroom. This is not surprising, given the complex nature of noise and the fact that different software uses different algorithms to find and reduce noise.  Granted, my camera is a few years old, and I should be upgrading it one of these days to one with a better sensor. But for now I have to work with what I have.


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## Tony Jay (Oct 13, 2014)

Hi Jim

You will see that I don't deny that any of the third-party options work.
I also make a big point of refocusing the issue of noise reduction as something that needs to be thought about and planned for across the entire workflow and not just post-processing.

I am pleased that you are able to get good results with your workflow.
I confess to printing large A2 size and bigger, and rarely have a noise issue that translates into poor print results despite using very high ISO's at times.
Perhaps using a 5D Mark III makes a difference too.
(I do remember my 40D was quite noisy but I still have all those files and remastering them with Process 2012 gives really good results.)

I also stress, that, in post-processing not to make the mistake of viewing noise reduction in isolation.
Image sharpening and noise reduction are absolutely two sides of the same coin and the adjustments for sharpening affect noise reduction and vica versa.

So, if your workflow is optimised to minimize the noise issue and more attention is still needed then I have no practical or philosophical objection to third-party noise reduction software, but with regard to the OP I think it is reasonably obvious that he is still learning about the capabilities of Lightroom at a fairly fundamental level.

Tony Jay


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