Function Description:

AI photo restoration leverages deep learning and image restoration algorithms to achieve

"accurate identification + natural restoration" of various photo flaws (such as fading,

damage, blurring, etc.). No professional photo editing skills are required to restore the clarity

and texture of photos. Core functions include:

Intelligent Problem Accurate Identification: Automatically detects the type and area of

problems in photos, including common issues in old photos such as yellowing and fading,

edge tearing, missing corners, scratches, and noise, as well as blurring, reflections (glass

reflections, oily faces), and stains (coffee stains, fingerprints) in everyday photos. No manual

marking by the user is needed to pinpoint the key areas for restoration, avoiding overlooking

details.

Specialized Restoration of Old Photos:

Faded/Yellowed Restoration:

For black and white photos and faded color photos, AI references color data from photos of

the same era to accurately restore the original color tone (e.g., restoring a warm yellow

background to an 80s family photo, restoring vivid and saturated colors to a 90s landscape

photo), without exaggeration or distortion;

Damage Repair:

For photos with tears, missing corners, or holes, it automatically repairs missing areas—for

example, repairing missing clothing corners or background sky textures in old photos. The

repaired content highly matches the original image's lighting angles and texture, with no

stitching artifacts;

Blur Reduction:

Addressing the issue of blurred faces and text in old photos, it uses detail enhancement

algorithms to restore facial textures (e.g., wrinkles, facial contours) and text clarity (e.g.,

dates and signatures on old photos), avoiding the "plastic" look caused by excessive

smoothing.

Everyday Photo Imperfection Optimization: Responding to requests such as "removing

scratches from the background," "eliminating reflections in shop window photos," and

"cleaning stains from clothing," AI accurately locates imperfection areas, preserving original

details (such as fabric texture and background layering) while repairing, avoiding disruption

of the overall image quality. It also supports enhancing the clarity of blurry landscape and

portrait photos, restoring the outlines of distant objects and the details of hair.

Flexible Operation and Texture Preservation:

Fine-tuning with prompts:

Users can add their own requests (e.g., "preserve the grain texture of old photos during

repair," "remove only glare from faces without changing skin tone"). AI adjusts the repair

intensity based on these prompts to meet personalized needs.

Real-time preview and comparison:

Users can view the results in real-time during the repair process, generating a split-screen

comparison of "original image vs. repaired image" to easily confirm whether it meets

expectations. Additional commands can be added at any time for further optimization.

Efficient Batch Processing:

Supports uploading multiple photos (such as a collection of old family photos), inputting

unified repair requests (e.g., "remove scratches and restore faded colors from all photos"),

and completing batch repairs significantly saves time.

            Old Picture

                Repaired