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Enlarging a small photo for a large print without quality loss.

A photo can look perfectly sharp on a monitor and still look noticeably softer when printed at 20 × 30 or 24 × 36 inches. When the source file doesn’t have enough resolution for that print size, enlarging it can make fine details look softer and edges less defined.

Wildlife is a good example. A 12MP DSLR can produce a perfectly usable photograph, but if the subject occupies only a small portion of the frame, cropping can leave only a fraction of the original pixels for the final image. The same thing can happen with a modern high-resolution camera- a 45MP file sounds like plenty, but a heavy crop can quickly reduce the resolution available for a large print.

I’ve tried standard resizing, sharpening, and dedicated AI upscaling tools to deal with this problem over the years. I can get very good results with Lightroom and Photoshop, too, especially when I’m willing to spend more time fine-tuning the image. The same is true of more specialized upscaling tools—the results can be excellent, but getting there sometimes takes a fair amount of hands-on work. So I was a little skeptical when I first tested Aiarty Image Enhancer.

After trying it on a range of photos, I was pleasantly surprised by how clean and natural the results looked. In many cases, I could move the enlarged file into the rest of my editing workflow without additional cleanup. It became a useful option when a cropped or low-resolution photo didn’t have enough pixels for the print size I wanted.

How Aiarty Enlarges Photos for Large Prints

When I prepare a photo for a larger print, I first look at how far the cropped file is from the pixel dimensions I need.

This is where I usually turn to Aiarty. If the file is only slightly short, I usually start with 2× rather than pushing the image further than necessary. For a heavily cropped or very small source, I may go to 4× or 8×, depending on how the result holds up. If I already know the final print dimensions, I can also set a custom output resolution and choose a suitable DPI for the final print workflow.

When enlarging a photo for a large print, things like high-ISO noise, compression artifacts, and slight softness can become much more obvious. I used to expect some cleanup after upscaling, but with Aiarty, I often get a cleaner starting point without having to spend as much time fixing those issues manually. I can then take the enlarged file into Lightroom or Photoshop for the final adjustments.

You can try Aiarty Image Enhancer for free to see how it enlarges your own photos before committing to a larger print. A 49% off lifetime license is also currently available for 3 PCs or Macs, with no subscription fee and free lifetime updates.

Real Test #1: Enlarging Wedding and Portrait Photos

Wedding and portrait photos are a good test for large-print enlargement because they are often printed as wall portraits or framed enlargements. Once I looked closely at the enlarged file, even small flaws in facial details, hair, and skin texture became easier to spot.

For this test, I started with a 3500 × 2333-pixel wedding photo. On paper, it’s a healthy file for standard albums. But when I checked the numbers for a 20 × 30-inch wall print, it dropped the native resolution to a meager 117 PPI. At that size, the print could look noticeably softer up close. 

Alt: Original wedding photo with blurry facial details at 180% zoom

I enlarged the image 2× with Aiarty, producing a 7000 × 4666-pixel file. At the same 20 × 30-inch print size, that increases the pixel density to about 233 PPI. That gave me a much more comfortable starting point for the 20 × 30-inch print than the original file.

Alt: 2× enlarged in Aiarty, More-Detail GAN model, Face Restoration enabled

Real Test #2: Enlarging a Cropped Wildlife Photo

Wildlife photography is a revealing test for photo enlargement because the subject often occupies only a small part of the frame. A high-resolution original can lose a significant amount of its available pixels after a tight crop.

Here, the cropped image was 1728 × 2592 pixels, taken from a much larger original. At 200% on screen, I could already see some noise and softness in the feathers.

I wanted to use it for a 16 × 24-inch wildlife wall print. So I enlarge it 2x to 3456 × 5184 pixels. The feather detail was easier to see, and the noise was less distracting. The additional pixels also provided more room for larger prints without changing the original composition.

Alt: Aiarty 2× enlarged wildlife photo, More-Detail GAN model

With feathers, I was careful not to push the sharpening too far, since it is easy to turn fine texture into something hard and artificial. I noticed that the sharpening could be adjusted based on how much detail was already there. That made it easier to stop once the image looked clearer without making the fine texture look unnaturally crisp.

Alt: Original photo 100% crop vs Aiarty 2× enlarged photo 100% crop

Real Test #3: Old Family Photos and Small Scans

Some of the most meaningful photographs were never captured at high resolution in the first place. Old family photos often exist as small scans or low-quality JPEGs, with faces already looking soft before any enlargement takes place.

Alt: Source old family photo, 640 × 427 pixels, all faces are blurry in the photo

The source image was only 640 × 427 pixels. The original was quite blurry, and the facial details were difficult to make out. Because the file was so small, I knew I would need more than a simple 2× enlargement if I wanted to make a useful framed print. I went with 4×, bringing the image to 2560 × 1708 pixels. The enlarged image looked noticeably clearer overall and was suitable for the larger print I had in mind.

The faces were the area I watched most closely, as they were already soft in the original scan. This is where I found Face Restoration particularly useful. It made the facial features easier to see while keeping them looking natural, and I could adjust the strength if the enhancement started to feel too strong.

At 8 × 12 inches, the 2560 × 1708-pixel output provides about 213 PPI, compared with only about 53 PPI from the original file. For me, that made the enlarged version much more practical for a framed print while still preserving the character of the original scan.

Alt: Aiarty 4× enlarged old photo, Face Restoration enabled (80% restoration strength)

Real Test #4: Product Photos for E-Commerce and Large Displays

Product photography is another area where low resolution can really bite you. If you need to repurpose a smaller product shot into a large display or poster, any softness or pixelation instantly makes the item look cheap and unpolished to potential buyers.

For this test, I used a 1920 × 2400-pixel photo of a doughnut. Even at 100%, some fine details looked soft and weren’t as clear as I wanted. I then enlarged the image 2× with Aiarty, bringing it to 3840 × 4800 pixels.

Alt: Aiarty 2× enlarged product photo, More-Detail GAN model, 2-Pass processing enabled

The source also had some visible noise and compression artifacts, so I decided to use 2-path processing rather than simply enlarging the file in one pass. After processing, the chocolate drizzle, colorful sprinkles, and doughnut texture looked cleaner and more polished, closer to what I would expect from a professionally finished product photo.

Alt: Original vs Aiarty 2× enlarged detail comparison of the doughnut photo

My Large-Print Workflow in Aiarty Image Enhancer

1. Start with the Best Original and Final Composition

Whenever possible, I start with the RAW file or highest-quality JPEG/TIFF rather than a compressed or social-media copy. I also make sure the image has the final framing I want before enlarging it.

If the photo needs to be cropped, I crop it first. The crop determines how many pixels I actually have available for the final print. If the composition is already right, I can simply move on to enlargement.

2. Calculate the Target Dimensions

I work backward from the final print size to estimate how many pixels I need and whether the image requires 2×, 4×, or a larger enlargement.

A Nikon D90, for example, produces 4288 × 2848 pixels. At around 150–200 PPI, that can already be enough for many large prints without enlargement. The main issue comes when the image is tightly cropped and much of that original resolution is lost.

Here are the pixel requirements for common print sizes at different PPI levels:

These are target dimensions rather than strict quality limits. A large wall print does not always need 300 PPI, especially when viewed from several feet away. Cropping, viewing distance, and print medium all affect the practical resolution needed.

For example, a 2000 × 3000-pixel crop printed at 16 × 24 inches provides about 125 PPI. A 2× enlargement brings it to 4000 × 6000 pixels, or about 250 PPI at the same size. This is a more typical situation where AI enlargement can help bring a cropped image closer to the target resolution.

3. Upscale and Fine-Tune in Aiarty

I start with the appropriate AI model and a moderate enlargement, then adjust the Strength Slider while checking details such as feathers, skin, product edges, or fine textures. If the image needs a quick crop, size adjustment, or minor color correction, I can also handle that here instead of moving the file between different apps.

Before exporting, the output DPI can be set according to the requirements of the print workflow. For more advanced retouching, I then move the enlarged file to Lightroom or Photoshop for final color and editing.

Final Thoughts

If you are planning to print your photos at a large size, you don’t necessarily have to be limited by the megapixels of your camera. As the examples above show, the right enlargement process can give a lower-resolution or heavily cropped image enough additional resolution for larger prints while keeping important details looking natural. Aiarty Image Enhancer is one option I use when a standard resize isn’t enough.

If you’re preparing photos for large prints, Aiarty Image Enhancer is currently 49% off at $79 (originally $155) for a lifetime license covering 3 computers. There’s no subscription fee, and lifetime updates are included.

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