Visible Near-Infrared Spectrum Dictionary for Real-Time Spectrometry
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Solution Overview
Problem
Existing imaging spectrometers are not suitable for real-time spectrum acquisition of distant moving targets or dynamic phenomena due to narrow computational spectrometry bands and complex systems that struggle with spatial and spectral encoding, leading to inefficient data processing and low signal-to-noise ratios.
Innovation Solution
A visible near-infrared spectrum dictionary is constructed using a four-primary color chromaticity cone with normalized spectral response curves, allowing for weighted combinations and discretization to form multi-scale spectrum curves, which are then clustered to generate phrases and sentences in the dictionary, enabling efficient real-time spectrum acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spectroscopic imaging spectrometers are used to achieve high spectral resolution, then spectral resolution is improved, but signal-to-noise ratio and light energy are reduced
Solution Approach 1:
The patent segments the spectral measurement process into multiple discrete wavelength channels detected simultaneously by an imaging sensor array. Each pixel in the sensor array captures spectral information at different wavelengths, enabling high spectral resolution without the sequential scanning that would reduce signal-to-noise ratio. This spatial-spectral segmentation allows parallel acquisition of multiple spectral bands.
Solution Approach 2:
The patent transitions from one-dimensional spectral scanning to two-dimensional spatial-spectral imaging. By adding the spatial dimension with multiple pixels detecting different wavelengths simultaneously, the system achieves high spectral resolution while maintaining high signal-to-noise ratio through parallel photon collection across the entire sensor array.
2Reliability
If Fourier interferometric imaging spectrometers are used to increase luminous flux and signal-to-noise ratio, then signal-to-noise ratio is improved, but system complexity increases
Solution Approach 1:
The patent extracts the spectral encoding function from complex interferometric hardware and implements it through simpler optical filters or diffraction gratings combined with an imaging sensor array. This removes the need for moving parts, precise mechanical control, and complex interferometric path management while maintaining spectral measurement capability.
Solution Approach 2:
The patent replaces the mechanical scanning and interferometric modulation systems with a static optical filtering approach. Instead of moving mirrors or modulators, the system uses fixed optical elements (filters, gratings) to disperse and detect spectral information, eliminating mechanical complexity while preserving spectral measurement functionality.
3Adaptability or versatility
If computational spectrometry imaging techniques are used to expand spectral coverage, then spectral bandwidth is improved, but computational complexity and data processing requirements increase
Solution Approach 1:
The patent performs spectral encoding and separation at the optical level before detection, using physical filters or gratings to pre-sort wavelengths to different spatial locations or detector regions. This preliminary optical processing reduces the computational burden by providing structured, partially decoded spectral data that requires minimal post-processing reconstruction.
4Power
If passive data acquisition and ground-based processing are used for moving targets, then data processing capability is improved, but data timeliness and target tracking capability are reduced
Solution Approach 1:
The patent implements a dynamic, distributed processing architecture where spectral data can be processed locally at multiple nodes (including on the platform carrying the sensor) rather than centralized ground processing. This enables real-time tracking and response to moving targets while maintaining high processing capability through parallel distributed computation.
Data Source
AI summary
A construction method and system for a visible near-infrared spectrum dictionary is provided. The method includes: constructing a four-primary color chromaticity cone by using normalized spectral response curves of four primary colors of a visible light camera as spectral basis functions; performing weighted combination on the spectral basis functions and forming an initial visible near-infrared spectrum dictionary; acquiring points on the four-primary color chromaticity cone on the basis of the initial visible red infrared spectrum dictionary according to different spectral resolutions and performing discretization, and forming words in the initial visible near-infrared spectrum dictionary; clustering chromaticity coordinates corresponding to the words into different groups, performing weighted combination on multi-scale spectral response curves corresponding to different group types, generating phrases or sentences in the dictionary, and generating a final visible near-infrared spectrum dictionary. The visible near-infrared spectrum dictionary can support a novel computational spectrometry imaging spectrometer.