Computational Imaging Spectrometer Using Coded Spectral Modulation
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Solution Overview
Problem
Hyperspectral imaging systems face challenges in achieving global, persistent coverage with rapid revisits due to the high cost and complexity of spaceborne imagers, limiting their deployment and effectiveness.
Innovation Solution
A computational reconfigurable imaging spectrometer (CRISP) approach that miniaturizes hyperspectral imaging spectroscopy using a dual-disperser reimaging design with a static coding mask, relying on platform motion or sensor scanning for coding diversity, enabling high sensitivity and compatibility with a broad range of wavelengths without active components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional pushbroom imaging spectrometers are used, then spectral measurement capability is achieved, but system cost and complexity increase significantly
Solution Approach 1:
The spectrometer is segmented into two separate dispersive elements (first dispersive element and second dispersive element) that disperse light in orthogonal directions, allowing the spectral information to be captured in a single snapshot rather than requiring sequential scanning. This segmentation enables the system to achieve spectral measurement capability while reducing mechanical complexity and cost.
Solution Approach 2:
The patent introduces a spatial encoding dimension by projecting the dispersed spectral information onto a spatially encoding element (such as a coded aperture or mask). This transforms the traditional one-dimensional spectral scan into a two-dimensional spatial-spectral encoding problem that can be solved computationally, eliminating the need for mechanical scanning and reducing system complexity.
2Area of stationary object
If detector array size is increased to improve area coverage, then field of view expands, but signal-to-noise ratio decreases due to reduced photons per detector
Solution Approach 1:
The patent merges spectral information from multiple wavelengths onto the same detector pixels by using a dual-disperser configuration with spatial encoding. This allows the system to accumulate photons across the spectral dimension while maintaining spatial resolution, effectively combining signals that would otherwise be distributed across different detectors, thereby improving signal-to-noise ratio while preserving area coverage.
Solution Approach 2:
The spatial encoding element creates multiple coded copies of the spectral information that are superimposed on the detector array. Through computational decoding, the system can separate these copies and reconstruct the spectral data, allowing the use of smaller, lower-cost detectors while maintaining measurement precision.
3Reliability
If uncooled detectors are used to reduce system complexity and cost, then detector reliability improves, but signal-to-noise ratio deteriorates due to higher noise levels
Solution Approach 1:
The patent replaces the thermal cooling mechanism with a computational approach. Instead of using cryogenic cooling to reduce detector noise, the system uses computational algorithms to separate signal from noise in the raw measurements. The dual-disperser spatial encoding provides redundant information that allows noise reduction through processing, enabling the use of reliable uncooled detectors while maintaining measurement precision.
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
The CRISP system achieves significant radiometric advantages, including increased signal-to-noise ratio (SNR) and multiplex advantages, making it competitive with conventional pushbroom imaging spectrometers, even with uncooled detectors, and allows for miniaturization and improved area coverage.
Implementation Method 1
separating an incident image into N spectral components propagating orthogonal to a direction of motion
Implementation Method 2
The coding mask encodes the N spectral components with a predetermined code, such as a binary Walsh-Hadamard S-matrix code or a random binary code
Implementation Method 3
The second dispersive element recombines the N spectral components into an encoded image
Implementation Method 4
a detector array, such as an uncooled microbolometer array configured to detect long-wave infrared radiation
Data Source
AI summary
Hyperspectral imaging spectrometers have applications in environmental monitoring, biomedical imaging, surveillance, biological or chemical hazard detection, agriculture, and minerology. Nevertheless, their high cost and complexity has limited the number of fielded spaceborne hyperspectral imagers. To address these challenges, the wide field-of-view (FOV) hyperspectral imaging spectrometers disclosed here use computational imaging techniques to get high performance from smaller, noisier, and less-expensive components (e.g., uncooled microbolometers). They use platform motion and spectrally coded focal-plane masks to temporally modulate the optical spectrum, enabling simultaneous measurement of multiple spectral bins. Demodulation of this coded pattern returns an optical spectrum in each pixel. As a result, these computational reconfigurable imaging spectrometers are more suitable for small space and air platforms with strict size, weight, and power constraints, as well as applications where smaller or less expensive packaging is desired.