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Sharpen AI by Topaz Labs – a Winner!

Not long ago, I had the opportunity to photograph Kiane, a lovely Minneapolis-based model. One of my favorite shots of her was spoiled because I missed the focus. (Note to self: avoid using manual focus lenses in situations that are risky.)

Enter Sharpen AI, a software product created by Topaz Labs. Their claim was sharpening ā€œrepair jobsā€ that border on the miraculous, so I thought I’d give them a try. I’ll cut to the chase and present the before and after. The left ā€˜beforeā€ side represents my best effort to sharpen the image in Lightroom, the right ā€œafterā€ image is with Sharpen AI by Topaz Labs.

I have seen some ā€œknock your socks offā€ examples, but this is not one of them. On a mobile device you won’t be able to see the difference, but on a desktop computer, particularly around her eyes and mouth, the difference is obvious. And it is exactly the difference between a shot that doesn’t quite make it, and one that does.

A side note or two. The image was shot on a Fuji X-E2. Results with Sharpen AI seemed to be better if I did not try to sharpen in Lightroom first, but this should be considered an early result. Also, Sharpen AI has three different sharpening ā€œspecialtyā€ modes and I would not have considered the softness in this image, (exposed at 1/250s) to be a result of motion blur. But Sharpen AI’s auto-detect said that stabilization mode was the best way to go, and indeed it was.

[twenty20 img1=”22753″ img2=”22757″ offset=”0.5″ before=”Before” after=”After”]

On the right is another example. Viewed from a desktop computer, the difference might be marginally noticeable, and on a phone is invisible. Now click on the image for a blow-up. The difference is obvious. (The left image is a little over-sharpened – I didn’t take the time to fix it.)  This helps illustrate an important point: sharpness is largely dependent on resolution, which is a function of viewing size and/or viewing distance.

This principle illustrates the “danger” of pixel-peeping; you can waste a lot of time and effort working to sharpen an image to use at a size or (less often) distance that renders the additional sharpening unnoticeable. Learning when and where it matters is key.