Imaging Mask With All-Pass And Filter Elements
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Solution Overview
Problem
Conventional image reconstruction methods using sensor arrays with filters struggle to achieve high accuracy, spatial resolution, and dynamic range, particularly in capturing and reconstructing images with multiple qualities of light such as intensity, wavelength, and polarization.
Innovation Solution
An imaging system and method employing a mask with a combination of all-pass and filter elements, where all-pass elements pass all qualities of electromagnetic radiation, and filter elements selectively remove specific qualities, allowing for simultaneous capture and reconstruction of high-resolution images using a pseudo-randomly distributed mask and advanced reconstruction algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional filter arrays (e.g., Bayer filter) are used to separate light qualities, then selective capture of specific light qualities is achieved, but measurement precision and dynamic range are limited
Solution Approach 1:
The mask is segmented into multiple types of elements (all-pass elements, polarization filters, spectral filters, intensity filters) distributed across the sensor array. Each element type captures specific light quality information, and the segmentation enables simultaneous capture of multiple light qualities without requiring complex multi-layer filter structures.
Solution Approach 2:
The mask elements serve multiple functions: all-pass elements capture full spectral and polarization information, while filter elements selectively capture specific qualities. This multi-functionality allows a single mask layer to perform what would otherwise require multiple filter layers, improving measurement precision without proportionally increasing device complexity.
2Measurement precision
If regular pattern filter arrays are used, then manufacturing is simplified, but image reconstruction accuracy and spatial resolution are compromised
Solution Approach 1:
The mask employs an irregular, non-repeating pattern of elements rather than a regular periodic structure. This asymmetric distribution prevents aliasing artifacts and improves spatial resolution by providing more diverse sampling of the optical field, while the fabrication process uses standard photolithography techniques to maintain ease of manufacture.
Solution Approach 2:
The mask design changes the spatial distribution parameter from periodic to random/irregular, which fundamentally improves image reconstruction accuracy by providing better sampling coverage. The fabrication parameters remain compatible with standard manufacturing processes, balancing improved performance with manufacturing feasibility.
3Reliability
If all light qualities are captured at each pixel, then complete information is obtained, but signal intensity is diluted and dynamic range is reduced
Solution Approach 1:
The system extracts specific light quality information using filter elements that selectively transmit only desired wavelengths or polarization states. This extraction concentrates the signal intensity for each quality type at dedicated sensor pixels, improving signal strength and dynamic range while maintaining the ability to capture multiple light qualities across the array.
Solution Approach 2:
The system adds a spatial dimension to light quality separation by distributing different filter types across the sensor array rather than stacking filters at each pixel. This dimensional approach allows each pixel to receive strong, quality-specific signals while the array as a whole captures comprehensive light quality information.
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 the reconstruction of high-precision, high-dynamic range images by leveraging the sparsity of natural imagery, providing improved accuracy and accuracy in image reconstruction compared to conventional methods.
Implementation Method 1
The plurality of second mask elements comprises a first group of second mask elements configured to filter electromagnetic radiation according to a first polarization and a second group of second mask elements configured to filter electromagnetic radiation according to a second polarization
Implementation Method 2
Each first mask element passes all qualities of electromagnetic radiation received at a respective first mask element to the sensor array
Implementation Method 3
The second mask elements remove one or more qualities of electromagnetic radiation received at respective second mask elements
Data Source
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AI summary
An imaging method includes receiving electromagnetic radiation with a plurality of qualities from a scene to be captured at a mask and passing a first portion of the received electromagnetic radiation having the plurality of qualities present in the received electromagnetic radiation through the mask. One or more qualities of the received electromagnetic radiation is removed from a second portion of the received electromagnetic radiation, and the second portion of the received electromagnetic radiation absent the one or more removed qualities is passed through the mask.