Hyperspectral Imaging via Event Camera Interferometry
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Solution Overview
Problem
Current hyperspectral imaging technologies face challenges in efficiently capturing and processing light spectra from dynamic scenes, particularly in real-time applications such as nighttime vehicle navigation, where they struggle to provide accurate and timely spectral data in visible and non-visible spectral ranges.
Innovation Solution
The integration of an interferometer with an event camera generates an event stream that is processed to produce hyperspectral images, using a demodulation and frequency transform technique to extract spectral data from temporospatial aggregates of events, enabling the reconstruction of input scenes across various spectral ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional hyperspectral imaging methods are used to capture light spectra from dynamic scenes, then spectral data can be obtained, but the system cannot provide accurate and timely spectral data in real-time applications
Solution Approach 1:
The patent employs an event camera that dynamically responds to changes in light intensity rather than capturing static frames at fixed intervals. This dynamic approach allows the system to adapt to changing scenes in real-time while maintaining spectral accuracy, resolving the contradiction between processing speed and measurement precision.
Solution Approach 2:
The system transforms the acquisition parameter from fixed-time frame capture to event-driven temporal sampling. By changing how spectral data is collected (from periodic frames to asynchronous events), the system achieves both real-time processing capability and accurate spectral measurement without the traditional trade-off.
2Adaptability or versatility
If an interferometer is integrated with a conventional camera, then spectral data can be captured, but the system struggles to process dynamic scenes effectively
Solution Approach 1:
The event camera's dynamic response to light changes enables the interferometer-camera system to effectively capture and process dynamic scenes. Each pixel independently responds to intensity changes, providing high temporal resolution that adapts to scene dynamics while maintaining processing efficiency.
Solution Approach 2:
The patent replaces the conventional frame-based mechanical scanning approach with an event-driven computational approach. This substitution eliminates the need for synchronized mechanical movement and complex timing, improving processing efficiency while enhancing adaptability to dynamic scenes.
3Measurement precision
If Fourier transform spectroscopy is used to obtain continuous intensity spectrum, then electromagnetic spectrum can be obtained for each pixel, but the system complexity increases
Solution Approach 1:
The patent replaces complex mechanical Fourier transform spectroscopy hardware with a computational approach using event cameras and frequency transform algorithms. This substitution maintains spectral resolution while significantly reducing mechanical complexity and improving system reliability.
Solution Approach 2:
The event camera acts as an intermediary that captures temporal information in a simplified manner, which is then processed computationally to achieve spectral resolution. This intermediary approach decouples the complexity of spectral analysis from the hardware, reducing overall system complexity 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
This approach allows for the generation of accurate hyperspectral images that can be used in real-time applications like nighttime vehicle navigation, providing enhanced spectral data processing and improved scene reconstruction in both visible and non-visible spectral ranges.
Implementation Method 1
In FT spectroscopy, an optical waveform is split into two collinear delayed replicas, whose interference pattern is measured by a detector as a function of their delay.
Data Source
AI summary
A technology is described for hyperspectral imaging. An example of the technology can include receiving an event stream of events from an event camera coupled to an interferometer. The event camera can receive light output from the interferometer and generate the event stream, comprising event data that corresponds to the light output. The events in the event stream can indicate a pixel that detected an event, a time of the event, and a polarity of change in brightness detected by the pixel. Spectral data can be generated for the events in the event stream using a demodulation and frequency transform to convert temporospatial aggregates of events in the event stream to frequency domain data that corresponds to an optical spectrum. A hyperspectral image of an input scene in a spectral range can be generated using the spectral data.