Time-Encoded Multiplexed Imaging for Hyperspectral Motion
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Solution Overview
Problem
Current wide-area motion imaging systems face challenges in achieving both large area coverage and wide spectral bandwidth due to limitations in sampling rate, spatial resolution, occlusions, and lighting changes, making it difficult to implement hyperspectral sensing capabilities in military or commercial platforms.
Innovation Solution
Time-encoded multiplexed imaging systems that use a spatial light modulator and a detector array to encode and decode light fields with temporal modulations, allowing for simultaneous measurement of multiple degrees of freedom without sacrificing spatial or temporal resolution, enabling faster and more efficient hyperspectral imaging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If dispersive grating spectrometer is used to cover large area with high spectral bands, then spectral resolution is improved, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent introduces time as an additional dimension for encoding spectral information. Instead of mapping only spatial and spectral dimensions, the system uses temporal modulation to encode multiple spectral bands simultaneously at each spatial location, enabling high spectral resolution without sacrificing signal-to-noise ratio through the use of compressed sensing and temporal multiplexing
2Measurement precision
If interferometric spectrometer is used for hyperspectral imaging, then spectral measurement capability is improved, but scan rate deteriorates
Solution Approach 1:
The patent applies compressed sensing theory to pre-encode spectral information in the temporal domain before detection. By using incoherent random modulation patterns and capturing only a subset of measurements, the system can reconstruct high-resolution spectral data at high scan rates without requiring slow mechanical scanning or sequential band acquisition
Solution Approach 2:
The system adds the temporal dimension to the traditional spatial-spectral imaging paradigm. By modulating light intensity in time according to compressed sensing patterns and using temporal multiplexing, the system achieves both high spectral measurement capability and high scan rates simultaneously
3Area of stationary object
If traditional imaging systems are used for wide area coverage, then area coverage is improved, but spatial resolution deteriorates
Solution Approach 1:
The patent employs temporal multiplexing to encode multiple spatial locations with different temporal patterns. By modulating light from different spatial positions with unique time-varying codes and using compressed sensing reconstruction, the system achieves high spatial resolution across wide area coverage, effectively adding the temporal dimension to overcome the traditional area-resolution tradeoff
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 rapid acquisition of high-resolution hyperspectral data with improved signal-to-noise ratio, allowing for effective wide-area hyperspectral motion imaging that surpasses the limitations of traditional dispersive and interferometric spectrometers.
Implementation Method 1
The SLM, which is disposed in the first plane, encodes the first point in the first plane with a first temporal modulation and encodes the second point in the first plane with a second temporal modulation different from the first temporal modulation
Data Source
AI summary
An imaging system uses a dynamically varying coded mask, such as a spatial light modulator (SLM), to time-encode multiple degrees of freedom of a light field in parallel and a detector and processor to decode the encoded information. The encoded information may be decoded at the pixel level (e.g., with independently modulated counters in each pixel), on a read-out integrated circuit coupled to the detector, or on a circuit external to the detector. For example, the SLM, detector, and processor may create modulation sequences representing a system of linear equations where the variables represent a degree of freedom of the light field that is being sensed. If the number of equations and variables form a fully determined or overdetermined system of linear equations, the system of linear equations' solution can be determined through a matrix inverse. Otherwise, a solution can be determined with compressed sensing reconstruction techniques with the constraint that the signal is sparse in the frequency domain.