Stray-light PSF Determination for Imaging Systems
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Imaging systems, including optical and x-ray systems, suffer from stray light flux misdirection, which degrades image contrast and accuracy due to factors like Fresnel reflections, diffraction, and scattering, and existing methods for correcting stray light are either computationally intensive or introduce additional errors.
Innovation Solution
A method and apparatus to determine the stray-light point-spread function (PSF) of an optical imaging system using a source with a discrete boundary, capturing images at various orientations and positions to estimate PSF parameters through a functional form model that accounts for stray light, diffraction, and aberrations, and corrects image data using a cost function minimization approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional stray light correction methods are used, then image contrast and accuracy are improved, but computational complexity and processing time increase significantly
Solution Approach 1:
The patent pre-determines the stray light point-spread function (PSF) through systematic measurement using edge targets at multiple positions and orientations. This PSF characterization is performed beforehand and stored for use in correcting actual images, avoiding the need for complex real-time calculations during image processing while maintaining high correction accuracy
Solution Approach 2:
The patent uses edge targets with known geometric shapes to create reference images that copy the stray light effects. By analyzing these reference images and comparing them with the known target geometry, the system derives the stray light PSF without needing to process the actual subject image, thus separating the correction methodology from the imaging task
2Productivity
If simple offset and gain manipulations are applied to correct stray light, then processing time is reduced, but color accuracy and image fidelity deteriorate
Solution Approach 1:
The patent replaces simple arithmetic operations (offset and gain manipulations) with a physics-based computational model that uses the determined stray light PSF. The correction is achieved through convolution operations with the PSF, which accurately models the physical stray light pathways while maintaining computational efficiency through pre-characterization
Solution Approach 2:
The patent transforms the correction approach by changing from uniform parameter adjustments (offset/gain) to spatially varying parameters derived from the PSF. The PSF contains position-dependent stray light characteristics that are applied to correct different regions of the image appropriately, preserving color accuracy while maintaining processing efficiency
3Measurement precision
If comprehensive stray light characterization is performed, then correction accuracy is improved, but measurement and data acquisition complexity increases
Solution Approach 1:
The patent segments the stray light characterization process into discrete measurement steps: capturing edge images at multiple field positions, then at multiple orientations, and processing them separately. This segmentation allows systematic collection of comprehensive data while keeping each measurement step simple and manageable
Solution Approach 2:
The patent uses a single edge target object that serves multiple functions: it provides known geometric features for reference, creates high-contrast edges for detecting stray light, and can be positioned at multiple locations to map the entire field of view. This universal test object simplifies the measurement apparatus while enabling comprehensive PSF characterization
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 characterizes and corrects stray light effects in imaging systems, improving image quality by accurately determining the PSF and compensating for stray flux, thereby enhancing contrast and accuracy.
Implementation Method 1
an optical system, x-ray systems, and computerized tomography systems
Implementation Method 2
The imaging device, such as a camera lens, including all of its optical, mechanical and electrical components, may convey flux from the object plane onto an image plane
Implementation Method 3
Fresnel reflections from optical-element surfaces, as noted in U.S. Pat. No. 6,829,393
Implementation Method 4
diffraction at aperture edges
Implementation Method 5
scattering from air bubbles in transparent glass or plastic lens elements
Data Source
AI summary
A method of determining the point-spread function (PSF) of an imaging system includes the steps of capturing image data, establishing an idealized source spot, establishing a functional form model, subtracting the captured image from the estimated image equation and determining a metric that measures the fit of the estimated image to the captured image. The functional form model may include both diffraction and aberration and stray light. The functional form model may be optimized to reduce the metric to an acceptable level.