Optical Imager Non-Uniformity Calibration via Overlapping Target Scanning
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Solution Overview
Problem
Existing methods for calibrating non-uniformity compensation (NUC) terms in optical imagers, such as those used in missile seekers, are inefficient as they require separate test chambers for calibration and moving target tests, increasing test time and cost, and struggle with scenes containing high spatial frequencies, leading to artifacts.
Innovation Solution
A system and method that scans a test scene with a target and background at different illumination levels in an overlapping pattern across the imager field of view, allowing each imager pixel to image multiple target and background levels, and uses cross-referencing and filtering to estimate and refine NUC terms, enabling calibration in the same test chamber as moving target tests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate vacuum test chambers are used for flood measurements and moving target tests, then calibration can be performed with uniform flood sources, but test time and cost increase significantly
Solution Approach 1:
The patent combines flood measurements and moving target tests into a single vacuum test chamber. The test scene includes both uniform regions (for flood measurements) and target regions (for moving target tests), allowing both types of measurements to be performed sequentially in the same chamber without requiring multiple chambers or moving the imager between locations.
Solution Approach 2:
The test chamber is designed to serve multiple functions: it can perform both uniform flood source measurements and moving target tests. The test scene is configured to provide both uniform illumination areas and target objects within the same field of view, making the chamber universal for both calibration modes.
2Adaptability or versatility
If the imager is moved between multiple vacuum test chambers, then different calibration tests can be performed, but test cost increases significantly
Solution Approach 1:
The patent merges multiple calibration test capabilities into a single vacuum test chamber. By including both uniform regions and target regions in the test scene, the chamber can perform both flood measurements and moving target tests without requiring separate chambers, thereby reducing overall test cost.
Solution Approach 2:
The test chamber is designed to be self-sufficient by incorporating all necessary test elements (uniform background regions and target regions) within a single chamber. This eliminates the need for external chambers or additional equipment, making the system more cost-effective.
3Measurement precision
If blurred image approach is used for offset compensation, then fixed-pattern noise is reduced, but scene and body-motion dependent artifacts appear in high spatial frequency content
Solution Approach 1:
The patent segments the test scene into distinct uniform regions and target regions. By analyzing pixel responses in uniform regions separately from target regions, the method can identify and compensate for fixed-pattern noise without mistakenly treating high spatial frequency target content as noise, thereby avoiding artifacts.
Solution Approach 2:
The patent applies different processing approaches to different regions of the scene. Uniform regions are used for offset compensation analysis, while target regions are preserved with their full spatial frequency content. This local differentiation allows accurate compensation without introducing artifacts in high spatial frequency areas.
Data Source
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AI summary
A system and method for moving target based non-uniformity calibration for optical images. The described approach allows for the use of the same test chamber to perform non-uniformity calibration and moving target tests. The current approach works by scanning a test scene having a target and a background at different intensity levels in an overlapping pattern across the imager FOV and cross-referencing multiple measurements of each pixel of a test scene as viewed by different pixels in the imager; each fully-compensated image pixel sees multiple different scene pixels and each scene pixel is seen by multiple imager pixels. For each fully-compensated imager pixel, an Nth order correlation is performed on the measured and estimate pixel response data to calculate the NUC terms. This approach is based on the simple yet novel premise that every fully-compensated pixel in the array that looks at the same thing should see the same thing.