Misregistration Correction in Line Scanning Imaging Systems
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Solution Overview
Problem
Existing electro-optical line scanning sensors face challenges in accurately correcting geometric artifacts caused by unprogrammed motion, such as vibrations and sensor attitude errors, which affect image quality and require separate estimation of linear, oscillatory, and random errors.
Innovation Solution
A method for misregistration correction (MRC) that estimates and corrects unprogrammed motion using a non-pinhole camera model, formulating scan motion over the focal plane with coupled non-linear scan equations and applying updates to coefficients based on image correlation, allowing for simultaneous estimation of sensor knowledge errors in position, velocity, and attitude angles without separating errors by category.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional pinhole camera model and linear scan equations are used, then the system is simpler to implement, but manufacturing precision and measurement precision deteriorate due to inability to accurately correct geometric artifacts from unprogrammed motion
Solution Approach 1:
The patent transforms the traditional linear scan equations into coupled non-linear scan equations by incorporating additional parameters that describe unprogrammed motion (vibrations, attitude errors). This allows the system to accurately model and correct geometric artifacts while maintaining computational tractability through the use of constant coefficients in the non-linear equations.
Solution Approach 2:
The patent segments the error correction process by separately estimating different types of unprogrammed motion (linear drift, oscillatory vibrations, random errors) through image correlation at detector junctions. This segmentation allows targeted correction of each error type while using a unified non-linear scan model framework.
2Measurement precision
If separate estimation of linear, oscillatory, and random errors is performed, then measurement precision may improve for specific error types, but device complexity and processing time increase
Solution Approach 1:
The patent merges the estimation of linear, oscillatory, and random errors into a unified non-linear scan equation framework. By using image correlation at detector junction overlap regions, the system simultaneously estimates all error types through a single coupled system of equations, eliminating the need for separate processing chains while maintaining precision.
Solution Approach 2:
The non-linear scan equations serve multiple functions simultaneously: they model programmed scan motion, characterize unprogrammed motion effects, and provide the basis for error estimation and correction. This multi-functionality reduces overall system complexity while maintaining comprehensive error correction capabilities.
3Manufacturing precision
If non-linear scan equations with constant coefficients are used, then manufacturing precision and measurement precision improve through accurate misregistration correction, but use of energy and computational resources increase
Solution Approach 1:
The patent changes the mathematical form of scan equations to have constant coefficients despite being non-linear. This allows the use of efficient numerical methods and pre-computation techniques, reducing real-time computational energy requirements while maintaining the accuracy benefits of non-linear modeling for geometric artifact correction.
4Measurement precision
If image correlation is performed at detector junction overlap regions, then measurement precision improves for motion estimation, but productivity decreases due to additional processing steps
Solution Approach 1:
The patent performs image correlation only at specific detector junction overlap regions rather than across the entire detector array. This partial action approach provides sufficient motion estimation precision for correction purposes while significantly reducing the computational burden compared to full-array correlation, thus maintaining productivity.
Data Source
AI summary
A method of misregistration correction in a line scanning imaging system includes: generating a model of scan motion over a focal plane of the imaging system, using a coupled system of non-linear scan equations with constant coefficients; estimating programmed motion positions across a plurality of detector junction overlap regions via a state transition matrix solution to the scan equations; at each detector junction overlap region, measuring actual motion positions via image correlation of overlapping detectors; generating differences between the actual motion positions and the estimated programmed motion positions; estimating updates to the constant coefficients based on the generated differences; generating corrections from the estimated updates to remove unwanted motion; and applying the updates to the constant coefficients.