Best Tools to Restore and Upscale Old Photos with AI

Why Old Photos Need More Than Upscaling

Old photographs present a unique challenge for AI upscalers because they combine multiple problems that need to be addressed before or alongside resolution enlargement. A typical scanned family photo from the 1960s or 1970s might be faded, yellowish, noisy from film grain, scratched from handling, and small in pixel dimensions because it was scanned at a low DPI. Simply running it through an AI upscaler without addressing these issues amplifies every flaw along with the image content.

Effective old photo restoration is a multi-step process: repair physical damage (scratches, tears, stains), correct fading and color shifts, reduce noise and grain, enhance faces that have lost detail, optionally add color to black-and-white images, and finally upscale to a modern resolution. Some tools handle multiple steps in a single pass, while others specialize in one stage of the pipeline.

Best Tools for Old Photo Restoration and Upscaling

Nero AI

Nero AI is the strongest all-in-one option for old photo work because it bundles upscaling, face enhancement, colorization, and artifact removal in a single application. The face enhancement feature is particularly important for old photos, where faces are often small, blurry, and faded. Nero's face-specific model detects faces in the image and applies targeted enhancement that produces natural-looking eyes, skin, and hair detail, even when the original face is only a few dozen pixels wide.

The colorization tool adds realistic color to black-and-white photographs. It works by analyzing the content of each region (sky, skin, foliage, clothing, architecture) and applying colors based on patterns learned from millions of color photographs. The results are not perfect and may not match the actual colors of the original scene, but they provide a convincing starting point that can be refined manually. Skin tones, sky gradients, and vegetation are typically handled well, while unusual clothing patterns and specific object colors may need adjustment.

Nero's upscaling engine supports up to 4x enlargement and produces clean results on standard photographic content. Combined with the face enhancement and colorization features, it can transform a small, faded, black-and-white scan into a sharp, colorful image that looks decades newer than the original.

Pricing includes a lifetime license for approximately $85 to $195, which is economical for anyone with a collection of old photos to restore. New accounts receive free credits for testing before purchase.

Topaz Gigapixel AI

For the upscaling stage specifically, Topaz Gigapixel produces the highest quality enlargements of well-preserved vintage photographs. Its face detection and enhancement is the best in the industry, producing realistic facial detail from very small source faces. The high-fidelity model preserves the character of vintage film grain and tonal transitions rather than aggressively smoothing them, which matters when you want the upscaled image to retain the aesthetic of the era.

Topaz does not include colorization or scratch repair, so it works best as part of a multi-tool workflow. Repair scratches and damage in Photoshop or GIMP, correct color and exposure in Lightroom or a free editor, then pass the cleaned image through Gigapixel for the final upscale. The combined Topaz Studio subscription ($149 per year) also includes DeNoise AI, which is excellent for reducing film grain before upscaling.

Remini

Remini gained popularity as a mobile app focused specifically on face enhancement and old photo restoration. Available on iOS and Android with a free tier, it uses AI to sharpen blurry faces and restore detail to degraded portraits. The results on face-focused images are impressive, particularly on very small or severely blurred faces where other tools produce uncanny output.

The limitation is that Remini is designed primarily for faces and portraits. It handles backgrounds and non-face content less impressively, and the free tier limits daily usage. For full-image restoration, it works best as a face-enhancement step in a larger workflow rather than as a standalone solution.

MyHeritage Photo Enhancer

MyHeritage, known primarily as a genealogy platform, offers AI photo enhancement and colorization tools designed specifically for historical and family photographs. The enhance feature sharpens faces and improves overall image quality, while the colorization tool adds natural-looking color to black-and-white images. Both tools are accessible through the MyHeritage website with a free tier that includes several images per month.

The genealogy context makes MyHeritage particularly well-suited for family photo restoration. The AI models appear to be optimized for the types of images genealogy users typically work with: formal portraits, group photos, wedding pictures, and snapshots from the mid-20th century. Face handling is strong, and the colorization produces natural results on common vintage photo subjects.

Free Tools for Old Photo Restoration

A capable free workflow for old photo restoration combines multiple tools:

GIMP (free, open source) for manual repair of scratches, tears, and stains using the clone stamp and healing tools. It also handles exposure correction, white balance adjustment, and basic noise reduction. GIMP requires more manual effort than AI-powered alternatives but gives you complete control over every aspect of the restoration.

Upscayl for the AI upscaling step. It handles the resolution enlargement well, and its noise reduction capabilities help with mild film grain. For severely grainy images, running a separate noise reduction pass before upscaling produces better results.

Palette.fm or DeOldify for free colorization. Both are available as web tools and produce decent colorization results on standard portraits and landscapes. DeOldify is open source and can be run locally for batch processing.

This free workflow requires more steps and manual work than an all-in-one paid tool, but it produces good results for users willing to invest the effort.

Scanning Tips for Best Restoration Results

If you have not yet scanned your old photos, the scanning process has a major impact on what AI tools can achieve.

Scan at 600 DPI or higher. Standard scanners default to 200 or 300 DPI, which is fine for document text but leaves detail on the table for photographs. Scanning at 600 DPI captures more of the original film detail, giving AI upscalers more information to work with. For small prints (wallet-size, 3x5), scan at 1200 DPI if your scanner supports it.

Scan as TIFF, not JPEG. JPEG compression destroys fine detail that AI upscalers need. TIFF files are larger but preserve everything the scanner captured. You can always convert to JPEG later, but you cannot recover detail that JPEG compression discarded during scanning.

Do not apply scanner auto-corrections. Many scanners offer automatic sharpening, color correction, and dust removal. Disable all of these and scan the raw, uncorrected image. AI tools perform these corrections better than scanner firmware, and scanner auto-corrections often make decisions that conflict with later AI processing.

Clean the scanner glass and the print. Dust and fingerprints on the scanner glass appear as dark spots in the scan, and AI upscalers will faithfully enlarge and sharpen them. Gently wipe the glass with a microfiber cloth and handle prints by the edges to minimize contamination.

Managing Expectations

AI restoration tools are genuinely impressive, but they have limits. A tiny, severely damaged print from the 1920s will not become a modern-quality photograph regardless of the tools used. The AI can generate plausible faces, textures, and colors, but the output reflects what the AI thinks the scene looked like, not what was actually there. Colors in colorized images are educated guesses. Facial features in heavily reconstructed faces are approximations. For personal memory and display purposes, these approximations are usually good enough. For historical documentation or identification purposes, treat AI-restored images as interpretations, not records.

The best results come from photos that are well-preserved but simply small or slightly faded. A clear, well-exposed 3x5 print from the 1980s scanned at 600 DPI will produce a stunning restored enlargement. A severely damaged, heavily faded 1x1 inch snapshot from the 1930s will produce an interesting approximation that may or may not resemble the original subject accurately.