Chromatic Aberration Analysis

Chromatic aberration (CA) is color fringing at high-contrast edges caused by lenses bending different wavelengths of light at slightly different angles. It's visible as red/cyan or blue/yellow fringes.

AI generates images pixel by pixel without simulating optical physics. There's no virtual lens to create chromatic aberration, resulting in unnaturally clean edges.

Even expensive lenses have some CA. While in-camera software may reduce visible CA, traces remain in the raw data, especially at wide apertures or frame edges.

Smartphones have small lenses with noticeable CA, especially at edges. However, computational photography often corrects this, reducing detection reliability.

By comparing red, green, and blue channel gradients at edges. Real CA shows consistent channel offsets; AI images have channels aligned perfectly at edges.

Software corrections reduce visible CA but leave residual patterns. Complete CA removal is difficult, so traces usually remain for forensic analysis.

Primarily lateral CA (color fringing increasing toward edges). Longitudinal CA (focus color shifts) is harder to detect but can provide additional signals.

CA correction is common in photo processing, and smartphone computational photography removes it. This makes CA absence less reliable as a standalone indicator.

AI could theoretically add CA post-generation, but current models don't. Even if added, fake CA patterns would likely differ from authentic lens CA characteristics.

Downscaling reduces CA visibility but doesn't eliminate it. Very small images may have insufficient detail for reliable CA analysis.