Flat-Field Correction (FFC) is a crucial process for image acquisition, addressing sensor and lens artifacts, and ensuring consistent image uniformity regardless of exposure settings.

How FFC Works

FFC primarily targets sensor artifacts, particularly in CMOS-based cameras where pixel performance discrepancies can be significant. The process involves creating “image-maps” within the camera itself, storing calibration data to equalize pixel response. Some cameras incorporate automatic loops to adjust for temperature fluctuations, a common source of calibration drift. Certain machine vision cameras even include in-field FFC algorithms to compensate for variations in optics and lighting.

Key Considerations

  • In-Camera vs. External Processing: While external processing via frame grabbers or CPUs/GPUs is possible, in-camera FFC offers greater accuracy and efficiency.
  • Bit Depth Matters: In-camera processing leverages 12-bit data, providing a significant advantage over later-stage 10-bit or 8-bit conversions.
  • Potential Trade-offs: Applying excessive gain corrections can inadvertently amplify noise, negatively impacting image uniformity and dynamic range.

Optimizing for Accuracy

Rather than solely relying on FFC to correct for non-uniformities, a more effective strategy involves proactively minimizing these issues at the sensor level. This includes understanding the specific characteristics of each sensor model and tailoring its performance to reduce the need for extensive FFC adjustments. The goal is to maintain spatial uniformity while preserving dynamic range and minimizing noise.

Source: Flat field correction on CMOS cameras – for better or for worse?