Infrared Focal Plane Array Bad Pixel Detection
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Solution Overview
Problem
Current methods for measuring performance parameters and detecting bad pixels in infrared focal plane array modules are inaccurate, especially when dealing with modules having two or more response areas, leading to errors in imaging quality and assessment.
Innovation Solution
A method involving an infrared imaging camera and computer system that captures continuous digital images, performs image division, and uses responsivity functions to measure performance parameters like signal transmission, temporal noise, spatial noise, and non-uniformity, while defining bad pixels based on gain and offset tables after two-point correction, and identifying pixels with abnormal noise values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the offset value method is used to detect bad pixels, then the detection process is simple, but it is not appropriate for infrared focal plane arrays with two or more response areas, leading to inaccurate detection
Solution Approach 1:
The patent divides the infrared focal plane array into multiple response areas based on actual responsivity characteristics. Each response area is then processed independently with its own statistical parameters (mean and standard deviation), allowing accurate bad pixel detection in each region without being affected by other regions with different characteristics.
Solution Approach 2:
The detection process is segmented into multiple steps: first dividing the array into response areas, then calculating statistical parameters for each area separately, and finally detecting bad pixels within each area using area-specific thresholds. This segmentation resolves the contradiction by making the simple statistical method applicable to multi-response-area arrays.
2Measurement precision
If the extreme value method or gain value method is used, then the detection covers the full range of pixel values, but pixels in different response areas cannot be properly distinguished, causing image distortion
Solution Approach 1:
The patent applies local quality by calculating statistical parameters (mean and standard deviation) separately for each response area. This allows the detection threshold to adapt to the local characteristics of each area, ensuring that pixels are evaluated relative to their own response area rather than being compared across areas with different gain and offset values, thus preventing image distortion.
3Manufacturing precision
If two-point correction is applied to correct gain and offset values, then the responsivity values of pixels can be corrected, but the different response areas still increase spatial and temporal noise
Solution Approach 1:
The patent addresses the noise issue by treating each response area independently. After two-point correction, each response area undergoes separate statistical analysis to determine its mean and standard deviation. Bad pixels are then detected using area-specific thresholds, which prevents noise from one response area from being misinterpreted as bad pixels in another response area, thereby reducing false detections.
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 enhances the accuracy of measuring performance parameters and reduces errors in detecting bad pixels, even in modules with multiple response areas, by correctly identifying pixel locations and numbers, thereby improving imaging quality.
Implementation Method 1
the energy of infrared light radiated from an object can be measured by an infrared detector
Implementation Method 2
The voltage values and current values obtained from the measurement of the infrared detector
Data Source
AI summary
A method for measuring performance parameters of an infrared focal plane array (IRFPA) module has steps of capturing continuous digital images from the IRFPA module, performing image division on each of the continuous digital images, and measuring multiple performance parameters of each divided digital image, including signal transmission function, a temporal noise equivalent temperature difference, a spatial noise equivalent temperature difference, non-uniformity and operability, thereby increasing accuracy in measuring the performance parameters of the IRFPA module. Also, a method for detecting bad pixels of an IRFPA module includes a gain value method, an offset value method, a temporal noise method and a spatial noise method, is applicable to the IRFPA module with more than two response areas, and avoids incorrect detection to treat pixels in different response areas as bad pixels.