Infrared Camera Fixed Pattern Noise Reduction
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Solution Overview
Problem
Infrared imaging cameras face challenges in correcting fixed pattern noise (FPN) due to pixel-to-pixel variations in responsivity and offset, which persist even when the camera is temperature stabilized, and are exacerbated by stray infrared radiation, making it difficult to produce high-quality images.
Innovation Solution
An iterative method is employed to determine and correct for fixed pattern noise by using live data from the sensor, applying an optimized correction factor to remove predictable and repeatable artifacts, which involves calculating adjusted sensor data through moving averages and objective function optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If temperature stabilization is applied to the camera, then thermal drift is reduced, but fixed pattern noise due to pixel-to-pixel variations in responsivity and offset persists
Solution Approach 1:
The patent applies preliminary action by performing FPN correction before final image output. The system captures raw sensor data, calculates correction factors based on scene uniformity assessment, and applies these corrections in advance to remove fixed pattern noise artifacts before the corrected image is displayed or stored.
Solution Approach 2:
The patent implements feedback by continuously monitoring scene uniformity and using this information to dynamically adjust correction factors. The system assesses whether the current scene is uniform or non-uniform, and selectively applies FPN correction only when appropriate, creating a closed-loop control system that optimizes image quality based on real-time conditions.
2Measurement precision
If traditional FPN correction methods are used, then some noise reduction is achieved, but severe artifacts in IRFPAs remain unusable
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting correction factors based on scene characteristics. Rather than using fixed correction values, the system modifies correction parameters in real-time based on assessed scene uniformity, allowing optimal correction for each specific imaging condition and enabling recovery of previously unusable severe artifacts.
Solution Approach 2:
The patent implements dynamics by transitioning from static FPN correction to a dynamic system that continuously adapts to changing scene conditions. The correction process responds to real-time assessments of scene uniformity, adjusting correction intensity and methodology based on current imaging conditions, thereby improving reliability across diverse scenarios.
3Measurement precision
If iterative correction with moving averages is applied, then fixed pattern noise is effectively removed, but processing complexity increases
Solution Approach 1:
The patent applies partial action by selectively applying full FPN correction only when scene uniformity exceeds a threshold. For non-uniform scenes, the system reduces or skips correction to avoid introducing artifacts, thereby reducing unnecessary processing complexity while maintaining high effectiveness for appropriate scenes.
Solution Approach 2:
The patent replaces complex mechanical processing with algorithmic substitution. Rather than using elaborate hardware-based correction mechanisms, the system uses software-based iterative correction with moving averages that can be implemented in standard processing units, reducing overall system complexity while maintaining high FPN removal effectiveness.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively removes fixed pattern noise from images, improving sensor performance and enabling the use of IRFPAs with severe artifacts that would otherwise be unusable, leading to better production yields and lower costs.
Implementation Method 1
An infrared detector called the 'bolometer,' now well known in the art, operates on the principle that the electrical resistance of the bolometer material changes with respect to the bolometer temperature, which in turn changes in response to the quantity of absorbed incident infrared radiation.
Implementation Method 2
These characteristics can be exploited to measure incident infrared radiation on the bolometer by sensing the resulting change in its resistance. When used as an infrared detector, the bolometer is generally thermally isolated from its supporting substrate or surroundings to allow the absorbed incident infrared radiation to generate a temperature change in the bolometer material, and be less affected by substrate temperature.
Data Source
Figure 1A~1D
Figure 2
Figure 3~4
AI summary
Methods and systems for correcting fixed pattern noise (FPN) in infrared (IR) imaging cameras. The methods and systems include correcting IR sensor data different strength levels of FPN data and selecting the particular strength level that produces corrected data with the least amount of FPN. The correction may occur over several frames of IR sensor data in order to find an optimal strength level for correction.