Beginning Note: A lot of these images will look better once enlarged, so I highly suggest viewing this post on a regular computer so you can click on each image and see the detail.

It will work on a smart phone or mobile device, but just be prepared to click on each image and zoom in – and you’ll be set!

Let’s face it. Not all lighting conditions are perfect. Sure, for a good portion of portraiture photography, you’re able to have pretty good control over the session’s lighting by use of off-camera flash, modifiers, studio lighting, etc.

But there are still times when either your equipment (or your location if you’re out of the studio) falls short of substantial amounts of light. Or if you also do weddings, you are all too aware of the effects of shooting in dark, non-ideal lighting conditions.

And your photos end up with a substantial amount of noise.

Sometimes, noise can be good, and can add another element of style to your images. But for the most part, it’s usually just really super annoying and degrades the quality of your image despite your best efforts to prevent it.

Programs like Lightroom do have a built-in noise reduction feature, but it can leave the subject’s skin looking a bit on the plastic-y side like the image shown on the right below (feel free to click to embiggen the image in a new tab to really see it well):

Photo courtesy of Amy Corrigan Photographer

I mean, sure, it worked, and the noise is gone, but it’s also a bit fake looking.

So how do you decrease the noise while still maintaining a real-looking photo (with non-plastic skin)?

Luckily, Imagenomics created a set of software to do just that – and it’s called Noiseware.

Yes, that’s right. The program is built just to handle photo noise.

I was able to take it for a spin recently and while I expected it to be a pretty cool piece of software, I wasn’t actually expecting it to be quite as thoroughly awesome as it really is.

Getting Started with Noiseware

Installation of the software was slick and easy. Literally, probably took me like, 30 seconds. To activate it in Photoshop (after you’ve imported a jpeg into Photoshop of course), you go through your Filters menu from Filters –> Imagenomics –> Noiseware.

And BOOM. You’re already rockin’ and rollin’.

Photo courtesy of Amy Corrigan Photographer

The plug-in is very easy to navigate, with three main sections you really need to pay attention to – the Settings panel (left-hand side), the image preview panel (center), and then the Navigator panel in the bottom right-hand corner that shows you where you are in the image in case you want to zoom in super far.

It’s not cluttered, it’s not complicated-looking, it’s laid out simply and elegantly. So we’re already off to a great start.

The Nitty Gritty

Once the image is brought into Noiseware, the software automatically calculates the amount of noise in the image and adjusts it accordingly. (Cool, right!?)

Which is why the image above already looks processed and like it doesn’t need any noise reduction – but you can actually see the original image here, and that it does contain some noise.

For images with a little to moderate amount of noise, I’ve found that the default import settings that the software applies are pretty spot on.

But of course, there are images that have a significant amount of noise, and some adjustments to the default need to be made.

First off, you can start with the presets, which are located in the upper left-hand corner at the top of the Settings panel. There’s a bunch of options to choose from, depending on whether the image you’re working with is a portrait, landscape, has a lot of noise, a little noise, etc.

noiseware-presetsAnd sometimes one of the presets will be good enough to do the job too.

But sometimes, it won’t. And this is where it gets really cool.

(…..ok I’m really excited about it, so just smile and pretend you’re excited too, ok?? For me??)

The Noise Level panel is where you control telling the software how much noise is present in the image, and the Noise Reduction panel allows you to actually perform the noise reduction.

Of course, the settings panel allows you to control the luminance for the overall image.

It also allows you to tell the software whether or not there’s more (or less) noise in the image than the software originally detected (that’s what the noise level box is for), giving you even more control over the image’s overall noise reduction. Like a filter, of sorts.

And then the Noise Reduction box allows you to perform the actual Noise Reduction on the image.

Below the main noise reduction panels, you’re left with the Detail, Frequency, and Tonal and Color Range panels.

I’m not going to go into great detail on each of these settings, but I will point out the parts of them that make Noiseware super ultra cool.

settings panel


The tab furthest to the left on the settings panel is the Detail panel.

This is where you protect the details in the image from being smoothed over when the software does its noise reduction.

Now, whereas the contrast slider leaves a bit to be desired, the sharpening option is pretty awesome, and can help redefine your edges once you’ve decided how much noise reduction your image needs.



The next tab over next to the Detail tab is the Frequency tab. And this is where you really get into the fine adjustments of the noise reduction.

When looking at noise in an image, there are predominantly four different sizes of noise grains – from the high frequency grains, which are the smallest, and the very low frequency grains, which are the largest.

The conditions under which the image was taken will affect the size of the noise and the dispersion throughout the image.

The frequency panel also works similarly to the main Noise Level and Noise Reduction box. The frequency Noise Level box allows you to tell the software if there is more (or less) noise in each frequency in the image than the software originally detected, and the Noise Reduction box allows you to control the amount of noise reduction for each frequency (or size of noise grain).

Clear as mud, right?

Let’s do some examples.

Screen Shot 2014-06-11 at 10.35.26 AM
Photo courtesy of Amy Corrigan Photographer

Take a look at the image above (and feel free to click the image to get a larger view as well). You can clearly see quite a bit of noise in the photo.

Looking at the size of the noise, I’m guessing that it falls within the mid- to high frequency range. So I’m going to increase the noise level and noise reduction in the mid- and high frequency range first, and see if that decreases the amount of grain.

Screen Shot 2014-06-11 at 10.36.14 AM
Photo courtesy of Amy Corrigan Photographer

Indeed, most of the noise has been removed from the image. The skin may be a bit smoother than I’d like; however, for instructional purposes this works fine.

Coincidentally, I’m guessing the original image had very little noise in the low and very low frequencies, but to make sure I’m going to reset the mid- and high frequencies and adjust the low and very low frequencies.

Screen Shot 2014-06-11 at 10.38.43 AM
Photo courtesy of Amy Corrigan Photographer

In the last image you’ll notice that the subject’s skin is smoother, but there’s more noise present than in the prior image. In the end, even though the majority of the noise lies in the higher frequencies, you’ll still want to adjust the lower frequencies alongside the higher ones to get optimal noise reduction.

And again, upon original startup of the plug-in the software will apply what it believes the optimal level of noise and noise reduction for each channel, and it may not even be something you need to tweak that much.

Tonal and Color Range

Screen Shot 2014-06-11 at 11.56.29 AM

The final tab in the lineup is the Tonal & Color Range tab.

Like the Frequency tab, it allows you to tell the software how much noise is present and then allows you to adjust the noise reduction in specific channels, except this time instead of it being for a frequency of noise, you’re changing the amount and level of noise reduction in the shadows, midtones, and highlights tones and in the seven color channels.

How cool is that?!

Ok, I thought it was super cool…..

I’ll give you a couple of examples.

Note the image below.

Photo courtesy of Tosha Cole Photography

You’ll notice a little bit of noise happening mostly around the subject, in the shadows tone and the blue color channel especially. So we have a little bit of noise here to work with.

First, I’ll give you an example of adjusting the noise within the shadow tone.

Photo courtesy of Tosha Cole Photography

In the photo to the left, you see the noise present in the shadows in the trees around the subject.

In the photo to the right, I told the software to reduce the noise in the shadows channel but not in the highlights or midtones channel, and you’ll see that the noise in the shadows to the left of the subject has been significantly decreased, whereas the change in noise on the subject’s face and skin is relatively untouched from one image to the next.

Oh yes, now you’re starting to get why this is so awesome!

One more example.

Photo courtesy of Tosha Cole Photography

In this image to the left, I told the software that there was very little noise in the red and yellow (aka ‘skin tone’) channels. Accordingly, the software did very little noise reduction in those color channels.

Then, in the image to the right, I did the exact opposite – I told the software there was a lot of noise in the skin tone color channels, and the software adjusted the noise reduction level accordingly.

You’ll also notice that from one image to the next the amount of noise in the white shirt and the black skirt is the same – which is because I didn’t tell the software to change the noise reduction level in the neutrals (black and white) channels.

I could have also done it the other way around, and left the skin tone channels the same and adjusted the noise reduction in the neutrals channels. I could even go in and fine-tune each of the seven color channels for maximum skin preservation (and to prevent that plastic skin tone look as much as possible).

Pretty Powerful Stuff, Huh?

By this point, you’ve seen some every in-depth examples of how much detailed control you have over the software and its ability to perform noise reduction.

The true power of the software, though, lies in its ability to control the amount of noise reduction that occurs on a subject’s skin – preventing that plastic-y fake look that is the side affect of some programs’ attempts at noise reduction.

In conclusion, I’ll leave you with some before-and-after shots to get a feel for overall image noise reduction. Enjoy!

Photo courtesy of Tosha Cole Photography
Photo courtesy of Amy Corrigan Photographer
Photo courtesy of Amy Corrigan Photographer
Photo courtesy of Amy Corrigan Photographer
Photo courtesy of Amy Corrigan Photographer
Photo courtesy of Amy Corrigan Photographer
Photo courtesy of Amy Corrigan Photographer

Bottom line?

This software really rocks.  As far as any downsides to the program, the contrast slider in the Details panel wasn’t really that awesome, and I’m still not entirely sure what the ‘color’ sliders change in the main Noise Reduction and Noise Level panel (top of the Settings panel).

However, the program’s ability to make such detailed adjustments far outweighs any of its shortcomings. This really is a must-have plug-in for any photographer at any level, since regardless of what kind of photography you shoot you’re bound to run into some non-ideal lighting conditions from time to time.

Ready to check it out for yourself?

Head on over to their website and give it a looksie!


P.S. Huge shout-out and thank you to Amy Corrigan and Tosha Lijewski for letting me use their images for the product review!




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Published by Beth Teutschmann

A big fan of food, chaos, and all things fun, Beth is the owner of Starboard Editing, LLC - a photography post-production company focusing on anything from editing to blogging and SEO. When she's required to leave the confines of her dark room, she enjoys martial arts, eating, tattoos, cooking, ice cream, sillyness, eating, and traveling. You should probably say hi.

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