Spectral Camera Mirror Array for Cross-Talk Reduction
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Solution Overview
Problem
Current hyperspectral cameras face challenges in efficiently acquiring 3D hyperspectral data cubes due to limited light throughput and time-consuming spatial scanning, requiring significant data storage and complex processing, and often suffer from cross-talk issues and the need for physical barriers to prevent optical duplication.
Innovation Solution
The use of an optical duplication system with mirrors to project multiple image copies onto a single sensor array, integrated with Fabry-Perot filters for reduced cross-talk and improved spectral resolution, allowing for simultaneous detection of multiple image channels and flexible reconfiguration for different spectral bands and resolutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If physical barriers are used to prevent cross-talk between image copies, then cross-talk is reduced, but device complexity and manufacturing difficulty increase
Solution Approach 1:
The patent removes the physical barrier component entirely and replaces it with an optical filtering approach using Fabry-Perot filters. Each sensor element has an integrated filter that selectively transmits specific wavelengths, preventing cross-talk through spectral separation rather than physical isolation. This extraction of the barrier function resolves the contradiction by eliminating structural complexity while maintaining cross-talk reduction.
Solution Approach 2:
The patent substitutes the mechanical/physical barrier system with an optical filtering system. Instead of using physical walls or masks to block light between adjacent image copies, the invention uses wavelength-selective Fabry-Perot filters at each sensor element to optically separate the spectral bands. This replacement of mechanical isolation with optical filtering reduces device complexity while achieving the same cross-talk prevention goal.
2Measurement precision
If spatial scanning is used to acquire hyperspectral data cubes, then spectral resolution is improved, but acquisition time and productivity decrease
Solution Approach 1:
The patent segments the spectral acquisition into multiple parallel optical channels, each dedicated to a specific wavelength band. By using an array of Fabry-Perot filters, each sensor element simultaneously captures a specific spectral band without requiring temporal scanning. This segmentation of the spectrum into parallel measurement channels resolves the contradiction by enabling high spectral resolution across all bands simultaneously, eliminating the time penalty of sequential scanning.
Solution Approach 2:
The patent transitions from temporal-multiplexed spectral acquisition (scanning through wavelengths over time) to spatially-parallel spectral acquisition (capturing multiple wavelengths simultaneously across a 2D sensor array). This dimensional change from time-based to space-based spectral separation enables simultaneous capture of the entire hyperspectral data cube, resolving the speed-resolution trade-off by adding spatial parallelism to the measurement process.
3Adaptability or versatility
If multiple image copies are projected onto a sensor array, then spectral detection capability is improved, but optical quality and manufacturing precision requirements increase
Solution Approach 1:
The patent makes each sensor element multi-functional by integrating a Fabry-Perot filter directly with the sensor. Each sensor-element-filter combination serves as an independent spectral detection unit that can be selectively activated for different wavelength bands. This universality allows the same sensor array structure to detect multiple spectral bands without requiring precise alignment between separate optical paths, as each element is self-contained and wavelength-selective by design.
Solution Approach 2:
The patent creates multiple spectral copies at the sensor plane through the use of multiple Fabry-Perot filters, each transmitting a different wavelength band to the same sensor array. Instead of projecting multiple spatial image copies that require precise optical alignment, the invention projects multiple spectral copies where each sensor element receives light filtered to a specific wavelength. This spectral copying approach reduces manufacturing precision requirements because the wavelength separation is achieved through the filter properties rather than through precise optical path alignment.
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 enables higher-speed acquisition of 3D hyperspectral data cubes with improved spectral and spatial resolution, reduced data storage needs, and simplified processing, while avoiding the need for physical barriers and enhancing optical quality and cost-effectiveness.
Implementation Method 1
integrated with Fabry-Perot filters for reduced cross-talk and improved spectral resolution
Implementation Method 2
an optical duplication system with mirrors to project multiple image copies onto a single sensor array
Data Source
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AI summary
A spectral camera for producing a spectral output has an objective lens (10) for producing an image, an array of mirrors (20), an array of filters (30) for passing a different passband of the optical spectrum for different ones of the optical channels arranged so as to project multiple of the optical channels onto different parts of the same focal plane, and a sensor array (40) at the focal plane o detect the filtered image copies simultaneously. By using mirrors, there may be less optical degradation and the trade off of cost with optical quality can be better. By projecting the optical channels onto different parts of the same focal plane a single sensor or coplanar multiple sensors can to be used to detect the different optical channels simultaneously which promotes simpler alignment and manufacturing.