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Topaz Labs

We just got a new AI software from Topaz Labs two days ago. We already had the Jpeg to RAW AI, AI Gigapixel and Sharpener AI from Topaz Labs. This one the Topaz Denoise AI, as the name suggest removes noise from your photos. It uses AI to remove noise without loosing detail and sharpness. So today I will share with you my impressions of it, and some comparisons to my currently most used noise reduction Photoshop plugins, the Imagenomic Noiseware. I don’t have many photos taken at high ISO settings, but there are some interiors and night shots where I had to use high ISO, so I will use those for the examples.

Topaz Denoise AI

Same as with other Topaz AI applications, the interface is very simple. You load your image and process it. You only have three sliders: remove noise, enhance sharpness and restore detail. They do exactly what the name suggests. There is also a brighten preview option, where you can have it brighten your photos, so you can see the noise better. This has no effect on the image processing, it’s just to make you work simpler.
Topaz Denoise AI
One nice feature here is the support for RAW images, so you can directly work on the source file. Better to do this before you did other edits on the image. You can save the export as a DNG file RAW afterwards.

Topaz Denoise AI

But let’s go to the examples. There are three images in every example. The original photo as TIFF (lens correction and chromatic aberrations removed before noise reduction, some brightened a bit to make the noise more visible). Second one is a Noiseware noise reduction with strong noise preset and detail protection set to 6. Last one is the Topaz Denoise AI result, with all the sliders at 0.25.

Please take the comparison between Noiseware and Denoise with reservations. You can set the sliders differently in both, and the results may greatly vary based on photo. There is no way I can show all the possible results here, so this should be taken just as small preview, and one should try both for oneself (there are trials available). I will focus here only on the Denoise results.

Please click on the images to see bigger versions, to see the noise.

Original
Original
Imagenomic Noiseware
Imagenomic Noiseware
Topaz Denoise AI
Topaz Denoise AI

In this interior photo, Topaz Denoise very nicely removed the noise and added quite nice structure to the pillars. Strangely, which I noticed in multiple photos, some lines caught a bit of a green color tint. You can see it in the middle here and also in the top right corner. Hard to say why this happens.

Original
Original
Imagenomic Noiseware
Imagenomic Noiseware
Topaz Denoise AI
Topaz Denoise AI

Here is a very noisy photo, taken in the middle of the night. Again, you can see how Denoise tries to add more structure to places that it removed noise from.

Original
Original
Imagenomic Noiseware
Imagenomic Noiseware
Topaz Denoise AI
Topaz Denoise AI

This is my favorite result here. The car looks so clean afterwards. All the detail is preserved and overall this is a great result.

Original
Original
Imagenomic Noiseware
Imagenomic Noiseware
Topaz Denoise AI
Topaz Denoise AI

This is a different example from the same photo as the previous example. Again, very nice result, very clean, very crisp.

Original
Original
Imagenomic Noiseware
Imagenomic Noiseware
Topaz Denoise AI
Topaz Denoise AI

One last example here (again from a car, really have very few photos taken at a higher ISO :)). Again a very nice clean result here.

My Impression

I quite like the Topaz Denoise AI results. It’s obvious it does more than just noise reduction. It looks for the structure, similar to other Topaz AI plugins, and tries to recover it after the noise reduction process. The results are really clean and good quality. And to think this is all with very weak noise reductions set at 0.25. You can go as high as 1.00 which just smooths out everything.

You can give Topaz Denoise a try by going to the Topaz Labs website and getting the trial version.

Long exposure reflection at the lake Bled

I’m not really happy with the photos I took at lake Bled last month, but I also would be sad if I did not edit at least some of them. But looks like I will have to go back to get some sort of a nice sunset there. Maybe later this year. Who knows :)

Here is another panorama with the church in the middle of the lake, nicely flanked by the mountains. This is a two shot panorama, each shot from a single exposure. Edited and merged in Photoshop. I used a 10 stop Formatt Hitech filter here, to blur the water.

Long exposure reflection at the lake Bled

And here are few details:

Long exposure reflection at the lake Bled

Why I don’t follow camera news anymore

There is so much camera news out there. New cameras, new lenses, rumors, updates, new gear and much more is released almost every day. And I don’t follow any of that anymore. I used to. Checking every new release, comparing it to what I had, wanting something different. But not for a long time now. And today I will share with you my reasons why I don’t care about this anymore.

Useless information

Do I really need to know the specs of every camera that is released? Of every lens? Do I even need to know that some camera was released? I have been using Canon cameras for about 10 years now, and I no longer even know what professional cameras Canon offers anymore. It’s useless to me. It will not make my photos better. Rather than reading up on this, I prefer to look at new editing techniques, processes, ways to improve, cool spots to visit, interesting compositions and similar.

Only time I look at this stuff now, is when I know need a new camera. When the shutter count is closing up to the camera limits, it’s time to have a look at something new. But other than that, why?

Gear envy

I know I had this. Seeing other photographers with pricey cameras, all the best gear, can make one feel envious. I felt the same before. But I don’t care anymore. There is a point, where what you have is good enough. The Canon 5D mark II, that I bought in 2012, is probably still good enough for most of what I do. And I still use it. Do I need a 30Mpix photo when doing photos at an event? Do I even need the 22Mpix the 5D mark II gives? It’s different for landscapes, but even there most of times you could get by.

Seeing all the new releases will only make you have more gear envy, that you don’t need at all. Focusing on what you have and how to get more from it, is much more rewarding in the end.

Diminishing returns

I think you all heard of the Law of diminishing returns. Here it would be, that there is a point where spending more on something, will get you almost nothing more. A good example would be tripods. Buying a 200 USD tripod, will give you a much better experience than a 40 USD tripod. It’s can easily be 5 times better. But how much better is a 1000 USD tripod than the 200 USD one? Maybe 2 times better? 1.5 times better? Maybe even less.

This goes hand in hand with gear envy and just useless information about all that is available. Do I need to know that if I spend double what I already did, I get something that is 5% better? No.

Pointless rumors

I hate rumors. And not just in camera news. They mean nothing. Do you know that Canon, Sony, Nikon and others will release new cameras? Of course they will. Will there be new versions of popular gear? Of course there will be. Will the new cameras be better? I do hope so. But do I need to know some random persons idea what they be? Not really. I seen rumor articles based on a single tweet from a new, never before used account. Really. News sites need content, and often they go with anything.

There has not been a big change in photography for a long time. I would count the switch to digital photography as one, but stuff like going mirror-less is just an evolution. You probably can predict every new camera that comes out just by looking at older releases. The changes are quite minor.

Minimalism

Over the last 1-2 years, I have been interested in scaling down. I got rid of a big pile of things. And I’m moving with this approach also to my digital life. I stopped using some social networks, unsubscribed from a lot of accounts on other sites, limited my visits to even more. And information on new cameras and gear just fits perfectly in a category I don’t need and can easily leave out.

Behind the camera

What I wanted to say with all of this, it’s better to focus on what you are doing and just ignore stuff that you don’t really have to care about.

Notre Dame fire

Really sad to see the photos and videos of the fire at the Notre Dame in Paris yesterday. Seeing such a big part of history and world heritage go up in flames is tragic. I do hope they try and rebuild it, even if it won’t be the same anymore.

Here are some of my older photos I posted of it. Better to remember it like this, than see it burning.

 

Notre Dame in Paris
Notre Dame in Paris
Notre Dame in Paris
Notre Dame in Paris

Notre Dame in Paris

And here is one more, I edited only today. This one is from under Pont des coeurs that is ring in front of the cathedral.

Notre Dame in Paris

Luminosity selections and masks

I use luminosity selections and luminosity masks in all my blending and editing, and today I will try to explain to you what they do and how to create them in Photoshop. But before I start, there is one requirement for understanding this guide. That is, you need to understand how layer masks work in Photoshop, as I will not go into their basics here. Please check this post about the basics of layer masks here to understand those.

Understanding Luminosity selections

In short, Luminosity masks are masks created from luminosity selections. These are selections based on brightness of pixels. The most basic luminosity selections would be then:

  • Bright – This selection selects every white pixel by 100%, every black pixel by 0%, and everything in between based on their brightness. So the brighter a pixel is, the more it is selected. So 25% grey pixel would be selected by 75%, 50% grey pixel would be selected by 50% and 75% grey pixel would be selected by 25%.
  • Dark – This is the inverse selection to the bright one. A white pixel is selected by 0% and a black pixel by 100%. Everything in between is selected based on how dark it is. So 25% grey pixel would be selected by 25%, 50% grey pixel would be selected by 50% and 75% grey pixel would be selected by 75%

These two selections split an image into two parts. The part that is mostly dark and the part that is mostly bright. A pixel with a 50% grey color, would be right in the middle, selected by 50% in both. I know it’s a bit hard to get the understanding of this, so let’s look at a very basic image, that illustrates this. This is a just a gradient from black to white.

Understanding Luminosity selections and masks

If we do the Bright and Dark selections here, there results would looks like this (this is already shown as a mask, as you can’t display opacity graduation in a selection, white means 100% selected, black means 0% selected).

Bright selection
Understanding Luminosity selections and masks
Dark selection
Understanding Luminosity selections and masks

As you can see on the Bright one, everywhere where it was bright in the original image, there is a shade of grey up to white. On the Dark one, you get the inverse, and it affects the areas that were dark. Let’s looks at one more example, this one with a regular photo.

Original photo
Understanding Luminosity selections and masks
Bright selection
Understanding Luminosity selections and masks
Dark selection
Understanding Luminosity selections and masks

You see the same effect. The Bright selection selects only the bright areas (clouds, snow), the Dark selection only the dark ones (mostly mountains).

There are also Midtone selections, which are created by subtracting Bright and Dark selections from a photo, but I will get to those in a separate article.

Refined Luminosity selections

You often here these selection being referred to as Bright 1, Bright 2, Bright 3 … Dark 1, Dark 2, Dark 3… and so on. In this context, the Bright selection I mentioned would be equal to Bright 1, the Dark to Dark 1. All others are refinement of these selection. By creating an intersection of a selection with itself, you create a new, more restrictive selection. So the higher the number here, the less is selected. On the gradient image I shown you earlier, the restricted masks would looks like this:

Bright 1
Understanding Luminosity selections and masks
Bright 2
Understanding Luminosity selections and masks
Bright 3
Understanding Luminosity selections and masks
Bright 4
Understanding Luminosity selections and masks

Creating Luminosity selections and masks in Photoshop

Ok, now that you hopefully at least have an idea on how luminosity selections look, let’s go into Photoshop and create some.

Open you image in Photoshop, and go into the Channels window. Here you will see 4 layers. The RGB, Red, Green and Blue. We want to work with the RGB one. Hold down Ctrl and click on it. This will create the Bright selection. Click on the Save selection as channel button in the bottom right (white square with black circle in the middle) and this will create a new channel. Let’s rename it to Bright 1.

Understanding Luminosity selections and masks

We will now work with this one. You should still have your selection active. Hold down Ctrl+Alt+Shift (a small X should be next to your cursor) and click on this new Bright 1 channel. The selection will change. Save it again as a new channel. Name the new channel Bright 2.

Understanding Luminosity selections and masks

You can now continue like this and create further, more restrictive selections, Bright 3, Bright 4, … and so on. If you ever loose your selection, just Ctrl+click on the one you want to restrict further, and the Ctrl+Alt+Shift+click on the same one again. Doing so on Bright 1 will create Bright 2, on Bright 2 will create Bright 3 and so on.

Understanding Luminosity selections and masks

Now onto the Dark selection. Go back to the RGB channel and Ctrl+click on it. This will create a Bright 1 selection. Now hit Ctrl+Shift+I on your keyboard (or select Select/Inverse from the menu). This will change the selection to the Dark 1 selection. You can create a new channel from this selection and call it Dark 1. To create all the other ones, just follow the same steps as when creating the Bright selections.

Understanding Luminosity selections and masks

If you want to avoid having to do this all the time, you can make it easier on yourself. Create actions that makes these masks, or buy Raya Pro or TK actions. Both of them create all the masks for you in one button press.

Once you have these channels, just choose one you want to work it and create a selection of it with Ctrl+click. If you want to make it into a layer mask, go back to layers with the selection active, choose the layer you want to use and click on Add layer mask (button looks the same as the one we used to create channels, in the bottom right of the layers window)

That’s all for today, next time I will show you how to use this in editing and blending of images.

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