Spatially Separated Spectral Arrays for Image Correction
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Solution Overview
Problem
Digital imaging systems face challenges in compensating for light source distortion, particularly in providing accurate spectral information to enhance camera performance and functionality, especially in applications like smart phones and high-resolution cameras.
Innovation Solution
The integration of interference-based filters, such as Fabry-Perot filters, with image sensors to create spatially separated spectral sub-arrays that provide localized bandpass responses across the sensor array, allowing for precise spectral imaging and correction of image data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If spectroscopy devices are used to detect multiple wavelength ranges, then spectral information is provided to assist camera functions, but the spatial resolution is compromised
Solution Approach 1:
The image sensor is divided into multiple spectral sub-arrays, each dedicated to detecting specific wavelength ranges. This segmentation allows different regions to specialize in capturing spectral information at different wavelengths, thereby providing comprehensive spectral data while maintaining spatial resolution through the distributed arrangement of these specialized sub-arrays across the sensor surface.
Solution Approach 2:
Each spectral sub-array is equipped with localized bandpass filters that are spatially separated and tuned to specific wavelength ranges. This local quality approach ensures that each region of the sensor optimally detects its assigned spectral band, providing precise spectral information without requiring the entire sensor to be optimized for all wavelengths, thus preserving spatial resolution.
2Loss of information
If interference-based filters are integrated with image sensors, then spectral information collection is improved, but device complexity increases
Solution Approach 1:
The complex spectral filtering function is segmented across multiple spatially separated spectral sub-arrays, with each sub-array containing a manageable number of interference-based filters tuned to specific wavelengths. This distributes the complexity across modular units rather than requiring a single complex filter system, making the overall system more manageable and manufacturable.
Solution Approach 2:
The image sensor is designed to perform multiple functions: standard color imaging and spectral detection. By integrating interference-based filters into the existing sensor architecture and using spatially separated spectral sub-arrays, the system achieves multi-functionality without requiring completely separate dedicated spectral imaging devices, thereby limiting the increase in device complexity.
3Loss of information
If spectral sensors with interference-based filters are used, then localized bandpass responses are achieved, but manufacturing precision requirements increase
Solution Approach 1:
The spectral detection function is segmented into multiple independent spectral sub-arrays distributed across the sensor. Each sub-array contains a limited set of interference filters that can be manufactured and aligned with relaxed precision requirements compared to a single comprehensive spectral system. This segmentation reduces the cumulative manufacturing precision burden.
Solution Approach 2:
The interference-based filters are integrated directly into the image sensor fabrication process, allowing the filters to self-align with the underlying photodetector elements during manufacturing. This integration enables the filters to serve their own alignment function, reducing the need for post-fabrication alignment procedures and lowering overall manufacturing precision requirements.
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 solution enables improved spectral imaging and correction, enhancing image quality and functionality in various applications by providing accurate spectral information without compromising spatial resolution.
Implementation Method 1
Interference-based filters, such as Fabry-Perot filters, when used in conjunction with spectral sensors have been shown to be capable of providing information that can be used for added camera performance and functionality
Implementation Method 2
Interference-based filters, such as Fabry-Perot filters
Data Source
AI summary
A system for imaging includes an array of optical sensors having a respective top surface and a respective bottom surface and a first plurality of sets of optical filters, each set of optical filters of the first plurality of sets of optical filters being associated with a respective set of optical sensors of the array. The system further includes a second plurality of sets of optical filters, each set of optical filters of the second plurality of sets of optical filters being associated with a respective set of optical sensors of the array, each optical filter of a set of optical filters of the second plurality of sets of optical filters configured to pass light of a respective wavelength range, where the second plurality of sets of optical filters are interspersed spatially across the top surface of the array of optical sensors. Finally, the system includes one or more processors adapted to sample an image of a scene based on an output from a first plurality of sets of optical sensors of the array and sample a received light spectrum for each set of optical sensors of a second plurality of sets of optical sensors of the array.