Pixelmator pro sharpen image4/19/2023 ![]() ![]() (See my review of Photoshop Super Resolution for a few comparisons). I haven’t tried Bigjpg but the other five all work similarly well as one another. I have no allegiance to any particular company, but there is one general class of upsampling algorithms that is way ahead of the competition these days: artificial intelligence upsampling.Īs far as I know, AI upsampling is available in five different software options at the moment: Adobe Lightroom, Adobe Photoshop, Adobe Camera Raw (which is part of Photoshop), Topaz Gigapixel, Pixelmator Pro, and Bigjpg. If you’re going to upsample, not all algorithms or software options are equally good. It didn’t exactly get sharper, but it did get less pixellated. Note how the detail looks before and after upsampling using the same “bicubic smoother” algorithm: Here’s a (very, very extreme) crop from a 24 megapixel image showing a palm leaf. Instead, upsampling can minimize pixellation and replace it with a bit of a blurriness instead. Just like before, upsampling doesn’t actually add more details to a photo, although some of the newer artificial intelligence algorithms come close. Even with a fairly high resolution sensor like a 24 megapixel DSLR or mirrorless camera, massive print sizes (in the range of 24×36 inches and up) can look a bit pixellated upon close inspection. Printing PhotosĪlong similar lines, pixellation can show up if you try to make a large print in photography. There are some artificial intelligence upsampling algorithms can do better – I’ll get to those in a moment – but there’s still no substitute for a high resolution starting image. The pixellation has been replaced with some general softness, which I find preferable.Īlthough this isn’t the best upsampling algorithm that exists today, it’s representative of a typical process (in this case, Photoshop’s “bicubic smoother” enlargement). ![]() This is a typical example scenario of what you’d be able to do with upsampling on a low resolution PNG (click to see larger):Īs you can see, it’s not a great improvement, but the second image does look a bit better. Rather than a jagged “stair step” of pixels along a diagonal line, upsampling can give you a bit of a smoother edge. But what you can do is decrease its pixilation. In general, the answer is no – there is no possible way to increase an image’s detail if it wasn’t there in the first place. If you come across a tiny image online (public domain hopefully) and you want to put it in a presentation or send to someone, you may be wondering if you can use an upsampling algorithm to increase its level of detail. The second is when you’re printing an image and want to avoid pixelation in the details. The first is when you’re working with a digital file that is extremely small, maybe just a few hundred pixels across. There are two major situations where upsampling an image is a good idea. It’s not something meant to be used all the time doing so would only take up space on your hard drive without meaningfully improving the quality of your images. Rather, upsampling is a fairly niche tool to solve a couple specific problems that you may come across occasionally when you work with images. Even if it could, you could just upsample the 48 megapixel image by a corresponding amount and still come out ahead! A 12 megapixel image will never contain as much detail as a comparable 48 megapixel image no matter how much you upsample it or what algorithms you use. However, upsampling isn’t a magic bullet. It’s most common in photography and graphic design to increase the resolution of an image, but it can also be used to increase the resolution of a video file (say, from 360p to 720p) or any other visual data. Upsampling is a tool in post-production software to increase resolution.
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