Infrared Bad Pixel Detection Without Mechanical Shutter
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Infrared imaging devices without mechanical shutters face challenges in detecting and correcting spurious pixels, which can degrade image quality over time due to physical modifications or mechanical damage, and existing methods are inefficient or impractical for shutter-less systems.
Innovation Solution
A method for detecting and correcting spurious pixels in infrared imaging devices involves receiving and correcting input images, calculating gain and offset correction values, and validating these values using a processing device to update the operability map and recalibrate affected pixels, without the need for a mechanical shutter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a mechanical shutter is used to detect spurious pixels during calibration periods, then spurious pixel detection accuracy is improved, but device complexity and cost increase, and fragility increases
Solution Approach 1:
The patent extracts the spurious pixel detection function from the mechanical shutter system and implements it through software algorithms processing continuous image data. The detection logic is separated from the mechanical calibration mechanism, allowing shutter-less operation while maintaining detection capability through statistical analysis of pixel behavior patterns across multiple frames.
Solution Approach 2:
The patent replaces the mechanical shutter system with an electronic/software-based detection system. Instead of using physical shutter closure to create uniform reference images for detection, the system uses computational methods to identify spurious pixels from normal image sequences, eliminating moving mechanical parts while achieving the same detection objective.
2Measurement precision
If a mechanical shutter is used for calibration periods, then spurious pixel detection is improved, but productivity decreases due to time loss during shutter closure
Solution Approach 1:
The patent enables continuous image capture and processing without interruption for mechanical shutter operation. The spurious pixel detection is performed continuously on incoming image frames through software analysis, eliminating the need to stop image acquisition for calibration periods, thereby maintaining uninterrupted productive operation.
Solution Approach 2:
The system performs preliminary spurious pixel detection and correction operations in the background during normal image capture, rather than requiring dedicated calibration time. By analyzing pixel statistics continuously and correcting spurious pixels in advance before final image output, the system maintains productivity while ensuring detection accuracy.
3Ease of operation
If spurious pixels are simply added to the bad pixels list, then detection simplicity is improved, but image quality deteriorates when spurious pixel density becomes significant
Solution Approach 1:
The patent applies different handling strategies to different types of defective pixels. Instead of uniformly treating all spurious pixels as bad pixels, the system categorizes them based on their characteristics and density, applying localized correction algorithms to regions with spurious pixels while preserving overall image quality. This differentiated approach maintains simplicity for individual pixel handling while ensuring quality when multiple spurious pixels are present.
Solution Approach 2:
The system applies partial correction to spurious pixels by interpolating values from neighboring pixels rather than completely replacing them, and applies this correction selectively based on spurious pixel density thresholds. This partial action approach prevents over-correction that would degrade image quality while still addressing the spurious pixel issue effectively.
Data Source
AI summary
The invention relates to a method for detecting bad pixels from a pixel array of a device, for capturing an image, that is sensitive to infrared radiation. The method includes: receiving an input image captured by the pixel system, and calculating a score for a plurality of target pixels including at least some of the pixels from the input image. The score for each target pixel is generated on the basis of k pixels of the input image that are selected in a window of H by H pixels around the target pixel. H is an odd integer greater than or equal to 3, and k is an integer between 2 and 5. Each pixel, from the set formed of the k pixels and the target pixel, share at least one border or corner with another pixel from said set, and the values of the k pixels are at respective distances from the value of the target pixel, the k pixels being selected on the basis of the k distances. The method also includes detecting that at least one of the target pixels is a bad pixel on the basis of the calculated scores.