Editorial & Image Review Methodology

Diagnose before recommending a workflow

Resolution, blur, noise, compression, physical damage, lighting and background separation are different image problems. Guidance begins by identifying the dominant defect and the final delivery requirement before suggesting enhancement, upscaling, denoise, deblur, restoration or another specialist workflow.

Use the source as the reference

The highest-quality original available remains the comparison point. Results are reviewed at matched zoom, at 100% around high-risk details and again at the size where the image will actually be delivered.

• Check eyes, teeth, hair and facial structure.
• Check text, logos and product markings character by character.
• Check fabric, foliage and repeated patterns for invented texture.
• Check edges and gradients for halos, fringing and banding.

Separate visual improvement from factual accuracy

AI can reconstruct plausible detail that was not clearly recorded by the source. Cleaner or sharper output is therefore not automatically more accurate. Reconstructed detail should not be treated as forensic evidence, identity proof or historically exact information.

Maintenance and corrections

Guides display update dates and are reviewed when supported formats, workflow controls, credit behavior, output limits or processing behavior change. Readers can report a technical error or outdated recommendation through the public contact page.