APPLICATION NOTE

Fixed Pattern Noise Correction
on Alvium Cameras

V1.0.02020-Mar-04

Scope
This document explains what fixed pattern noise (FPN) is and how the fixed pattern noise correction (FPNC)
is calibrated on Alvium cameras.

What is fixed pattern noise?
Some pixels on a sensor produce brighter intensities than the neighboring pixels. This spatial nonuniformity is called fixed pattern noise. It becomes visible on images acquired in the dark. Inaccuracies inthe pixel geometry and the sensor electronics create this effect.
FPN is a high-frequency signal overlaying the image signal. It increases with temperature and exposure
time. Though non-uniformities can occur on any individual pixel, issues apply typically to columns, due toreadout and amplification. Different sensors have individual characteristics. FPN divides into:
Illumination

DefectDescription

Dark image

Dark signal non-uniformity (DSNU)

Spatial variation of the dark signal

Bright image

Photo response non-uniformity (PRNU)

Spatial variation of the sensitivity

Example images
The following images show an ideal image (1), column noise and row noise (2), and pixel noise (3):1

2

3Figure 1: Ideal image and images with noise

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Fixed Pattern Noise Correction
on Alvium Cameras

How are Alvium cameras calibrated for FPNC?
The FPNC on Alvium cameras strives to correct FPN without damaging image details. All Alvium cameras arefactory calibrated using the following workflow. Depending on the dominant FPN of the sensor, either row
or column noise is being corrected. The following example relates to columns.
For all calibration steps, numerous images are averaged to compensate for temporal noise. In reality allcolumns of a sensor are corrected, the example shows the photo response of two averaged columns:
Gray value

Black level set points/ƌƌĂĚŝĂƟŽŶ
Change to be applied

Figure 2: Image before correction with two columns. Black level and slope differ.
1. Dark image: DSNU parameters are calculated.
Gray valueůĂĐŬůĞǀĞůƐĞƚƉŽŝŶƚƐ
/ƌƌĂĚŝĂƟŽŶ
ŚĂŶŐĞƚŽďĞĂƉƉůŝĞĚ

Figure 3: DSNU corrected image. Black level has been aligned, slope differs.
2. Bright image: PRNU parameters are calculated.
3. The corrections align different black levels and slopes.
Gray valueůĂĐŬůĞǀĞůƐĞƚƉŽŝŶƚƐ
/ƌƌĂĚŝĂƟŽŶ

Figure 4: PRNU corrected image. The columns show equal photo response.

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Fixed Pattern Noise Correction
on Alvium Cameras

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