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Topaz Tutorial: Editing Landscapes with Miroslav Petrasko

Landscape photos are quite different from cityscape photos. If you are not shooting right into the sun, you usually have much less local contrast and extreme differences in brightness in the photos. You can’t just take one and be done with it, so some editing is always required–even if it’s only to fix lens problems.

Sharpness is really important in landscape photos. Together with a bigger depth of field, it makes landscape photos stand out more. Here is where Topaz Sharpen AI can come in handy.

A Stunning View

This is a view from the Five Fingers lookout platform in the Austrian Alps, high above the town of Hallstatt. It was taken during an overcast day, so while it’s properly exposed, it’s a bit dark, hazy and bland. I won’t go through every edit I did on these photos, but will point out some of the most important techniques to help you get more from your landscape photos.

Original Image (Click to view at 100%)

I took three exposures for this photo in 1EV increments. I could have gotten away with just using a single exposure, but I knew I would want to lighten and darken certain areas. So, having a proper exposure of every area makes for a cleaner photo than one that was over or underexposed in post-processing. Here are the two additional exposures.

(Click to view at 100%)
(Click to view at 100%)

There is a photo post-processing technique called matching, which I’ll show you below. By doing so, you end up with a nice even blend that looks like one seamless photo. The idea behind it is to take the RAW files as smart objects into Photoshop and blend them together to get the desired exposure everywhere. 

(Click to view at 100%)

Once this is done, you go back into the RAW editor and tweak the RAW files, to create a similar look for each one. You do this by mostly tweaking the exposure, highlights, and shadows. You can also add enhancements like vibrance, dehaze and clarity to the RAWs, to make further editing even easier.

(Click to view at 100%)

I blended the photos into one by using layer masks and luminosity selections. Once done, I matched the exposures and added vibrance, clarity, and dehaze to them. Above is a screenshot of the blended, tweaked underexposed RAW and below is how it looked afterward. You can see that the blend has almost no contrast to it. That is normal because when you remove highlights and shadows, you also remove contrast. 

(Click to view at 100%)

From this point on, all of my edits are just tweaking brightness and contrast, maybe a bit of saturation here and there. Usually, you don’t need to edit saturation at all, as adding contrast makes the photo more saturated on its own. But as this was very overcast, I wanted the foreground color to stand more.

(Click to view at 100%)

You can see in this Photoshop screenshot all the layers I used and how I only painted them by hand to the areas I needed them in.

Best Practices for Sharpening

With this done, we’ll move on to sharpening. There are three things to consider here. Firstly, the whole photo should not be of the same sharpness. Our eyes are drawn towards sharper (and brighter) areas so you can use that to draw it towards your main subject. In this photo, that would mostly be the foreground and the middle area around the lake.

Secondly, not everything should be sharp. For instance, you would not expect the peaks in the further background to be as sharp as the closer ones. And you wouldn’t expect to have much darker clouds than the rest of the scenery.

Thirdly, it is good practice to resize the photo to your final desired resolution and only afterwards sharpen it. 

Topaz Sharpen AI

Let’s sharpen this photo now. We need to merge all the layers into a new one, and then use Topaz Sharpen AI from the plugin menu. There are multiple processing modes available in Sharpen AI to target specific problems–Sharpen, Stabilize, and Focus.

With a landscape photo, you can use all of them. For instance, if you got your focus a tiny bit off, you can try the focus mode to return some sharpness to the out of focus areas. Or perhaps you had a bit of wind come through and the foliage moved. In that case, you can try the stabilize mode.

Sharpening in Topaz Sharpen AI (Click to view at 100%)

For this photo, let’s go for the standard Sharpen mode. The standard settings look a bit strong for this photo, so let’s move the Remove Blur slider to 0.4. You can see a few areas in comparison below, all are at 100% zoom.

(Click to view at 100%)
(Click to view at 100%)

We can remove the sharpness from the areas where it’s not needed, and tone it down in others. You can choose to go back to Photoshop and remove the sharpness from the clouds, if you want them to be a bit blurry and soft. I also removed the sharpness from the peaks in the distance and toned it down on the peaks that are close. Like this, there is a nice progression, with the sharpest things close to you, losing the sharpness the further away you look.

The Final Result

Final Result (Click to view at 100%)

About Miroslav Petrasko

While I started as a game designer, I switched to photography around 10 years ago. Since then I have been working with different luxury travel brands and almost daily, stubbornly updating my blog at hdrshooter.com with new photos, articles, and guides. It really is not an easy task.

Below are a few other landscape photos from my travels. The first three are from Austria: the view from Dürnstein Castle, Grossglockner High Alpine Road and the reflection at Altaussee. The last two are from Switzerland: the peaks over Zermatt and Matterhorn.

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Let AI Sharpen Your Photos

As photographers, we want to shoot sharp photos, period!  Our goal of getting sharp images is one of the major factors in the thousands of dollars we spend on good cameras and lenses with features like optical stabilization.  We’ve also invested time in learning techniques, tips, and tools for shooting sharp photos, like lugging around a sturdy but heavy tripod, setting proper shutter speed, learning about depths of field, proper focus, and so on and so forth.

Even with the best equipment and expert techniques, we sometimes still end up with images that could be sharper. That is why almost every photo editing software provides a “Sharpen” feature.  For example, Photoshop has no less than 6 different “sharpen” filters on my last count.

While we hope that getting a sharp picture will not be a problem when using a sharpening software, we know that’s not always the case.  Unless your image has a very small blur, existing software “Sharpen” functions do not work well.

Now let’s go into a technical explanation about how a given software sharpens your images. Up until now, the photo sharpening tools in software typically use one of two type methods: image filtering or deconvolution.

The first type of sharpening is Image Filtering. The basic idea is simple: blurry images lack spatial high-frequency components.  Therefore, applying a filter that boosts high-frequency will make the photo look sharper. Generally, this technique will works for photos with just a little blur.  Since this method is fast, most software sharpen tools use this method. In Photoshop, “Sharpen”, “Sharpen More”, “Sharpen Edge” and “Unsharp Mask” all use this type.  

Figure 1 (click to view details at 100%)

The Image Filtering method works well if you just need to sharpen the photo slightly, but if your photo has a bigger blur, it does not work well.  The problem is that when boosting high-frequency photo components, the tool will also also boost noise and artifacts in photos. Over using a sharpening filter that uses this method will create images with artifacts such as “fat edges”, “halo”, and noise amplification.

The second type of sharpening method is called Deconvolution.   Imagine you are looking through a camera at a star at night.  You will see, instead of a single bright point, a small blurry disk.  This disk represents the so-called point spread function. This function summarizes the blurring process as a mathematical operation called Convolution. Thus, removing blur is modeled mathematically as Deconvolution. This type of method was first developed primarily for astronomy and later for spy satellites. At its creation, normal photographers did not have access to this tech due to the computer speed and the stability of the algorithms.

The situation changed around 2010. There was a break-through in the deconvolution algorithm to make it feasible to use on a PC.  We were the first company to bring this tech to photographers when we released a Photoshop plugin, Topaz InFocus. This method works much better for small and moderate blurs.  It also works, to a certain degree, on blur due to camera shake or from a moving object. To this day, Topaz InFocus is still be considered to be one of the best sharpening tools on the market. Later, Photoshop also added “Smart Sharpen” and “Shake Reduction” based on deconvolution.

Figure 2. Large motion blur (click to view at 100%)

In addition to being much slower than the image filtering method, deconvolution needs to know the point spread function, which is very hard to estimate. It is also very sensitive to image noise and jpeg compression.  Therefore, it fails most of the time for large and complex blurs, such as one in Figure 2 (a). Since Hollywood’s crime dramas had (incorrectly) shown that they could usually turn very blurry photos into sharp ones to catch the bad guys, Topaz InFocus fell short of some of our customers expectations.  I took this quite personally and have been on the lookout for a silver-bullet ever since.

For eight years we did not find one…. not until recently. I felt we might finally have a shot to redeem ourselves thanks to the rapid development of Deep Learning in Artificial Intelligence (AI).

AI approaches the problem very differently. Instead of studying the mathematical model of the blur process and how to solve the inverse problem, we train an Artificial Neural Network with millions of blur-sharp image pairs.  The neural network will eventually “remember” what the sharp image should look like if it sees a blurry image. After months of training, the neural network could produce a sharper when image given an image it had not seen before. Figure 1 (c) and Figure 2 (c) are examples from our latest product, Topaz Sharpen AI.   Here is another example to sharpen an out-of-focus photo.

Figure 3. Out-of-focus blur (click for 100%)

Looking at Figures 1, 2, and 3 more carefully, you will find that Topaz Sharpen AI seems be able to create images with very fine details rather than simply sharpening the edges.  This is what makes Topaz Sharpen AI truly unique – it actually synthesizes convincing details even if the blurred image does not have any through the power of AI.

There is a reason that nobody has released an deep-learning sharpen AI tool for photographers so far.  It is quite an engineering challenge. For example, the neural network requires extremely high computation that makes regular PC pretty much unusable.  I am so proud that our team was able to overcome many challenges to bring Topaz Sharpen AI to you, from Dr. Acharjee’s  ingenious neural network architecture, to Image Processing Lead Bowen Wang’s efficient GPU neural engine development, to our whole product team’s application design.

You can try it yourself by downloading the 30-day free trial.  For anyone who owns Topaz InFocus or the complete bundle, it’s a free upgrade!

Does AI finally make blurry images a thing of the past? Not at all.  The example images I used are pretty much the best case scenarios to impress you with the AI.  You will find it is still a hit or miss situation sometimes. However, it is a huge step forward when comparing with any existing solution, including our Topaz InFocus. And best of all, we are just at the beginning of the Artificial Intelligence (AI) revolution.  You can be assured that there will be many more amazing things to come.

About the Author

Albert Yang founded Topaz Labs over 10 years ago, to form a company that adopts and implements the latest technology to introduce cutting-edge tools to the Photo market. With over 30 years of programming experience, he’s proud to offer his technical expertise to our users as the primary developer of our latest tools.