Upscaling a photo isn't as simple as resizing in your default image viewer. While tools like the Mac or Windows photo viewer can increase image size, the results are often inconsistent, especially with old family photos or pixel art.

Traditional upscaling works by adding new pixels based on surrounding ones. Nearest-neighbor is best for pixel art and diagrams but causes aliasing on regular photos. Bilinear upscaling averages four surrounding pixels, producing smoother images but potentially softening details. Bicubic upscaling, which considers 16 surrounding pixels with weighted importance, offers a good balance of quality and resource usage for most photos.

AI upscaling uses prediction models trained on millions of high-resolution images. It can clean up degraded photos by removing grain while increasing resolution. However, AI upscalers can introduce unintended elements, like adding eyes to blurred faces, making them unsuitable for images requiring accuracy.

Image format selection matters too. JPEG is widely compatible but lossy. PNG supports transparency and maintains quality during editing. WebP offers smaller file sizes for web use. HEIC is ideal for Apple users but has limited cross-platform compatibility.