Intrinsic Spectral Signature Normalization Across Wavelength Ranges
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Solution Overview
Problem
Current spectroscopy and spectral imaging technologies face limitations in obtaining a full-range intrinsic spectral signature due to irrelevant spectral components from illumination, background, and instrument noise, which hinder the clarity and accuracy of material identification.
Innovation Solution
A method that balances and normalizes spectroscopic instruments to eliminate irrelevant components, allowing for the construction of a full-range intrinsic spectrum by isolating and quantifying instrument noise, and combining spectra across different wavelength ranges without the need for post-acquisition modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If spectroscopic instruments are used to obtain spectral data, then spectral information can be acquired, but irrelevant spectral components from illumination, background, and instrument noise reduce signal to noise ratio
Solution Approach 1:
The patent segments the spectral measurement process into distinct components: illumination spectrum measurement, sample spectrum measurement, and intrinsic spectrum calculation. By dividing the measurement into separate steps and isolating each spectral component, the method enables selective elimination of irrelevant components (illumination and background) while preserving the intrinsic sample spectrum, thereby improving signal to noise ratio without requiring complex real-time filtering during acquisition.
Solution Approach 2:
The patent extracts the intrinsic spectral signature by removing irrelevant spectral components through mathematical operations. Specifically, the illumination spectrum is subtracted from the measured sample spectrum, and background contributions are eliminated, leaving only the intrinsic spectral features of the sample material. This extraction process directly improves signal to noise ratio by isolating the relevant spectral information from contaminating components.
2Adaptability or versatility
If multiple spectroscopic instruments covering different wavelength ranges are used, then full electromagnetic spectrum coverage can be achieved, but consistency and normalization across instruments become problematic
Solution Approach 1:
The patent establishes a universal normalization procedure that can be applied across multiple spectroscopic instruments covering different wavelength ranges (UV-Vis, IR, microwave). By using the illumination spectrum as a common reference and applying consistent mathematical transformations, the method enables different instruments to produce comparable intrinsic spectral signatures, achieving full electromagnetic spectrum coverage while maintaining measurement consistency across all devices.
Solution Approach 2:
The patent transforms spectral data from different wavelength ranges by changing parameters such as intensity normalization and wavelength scaling. The illumination spectrum serves as a reference for normalizing intensities across instruments, and mathematical transformations are applied to ensure that intrinsic spectral signatures from UV-Vis, IR, and microwave instruments can be combined into a coherent full-range spectrum, resolving consistency issues between different measurement systems.
3Loss of information
If traditional spectral imaging methods are used, then spatial and spectral data can be obtained, but irrelevant components impede clear identification of materials
Solution Approach 1:
The patent performs preliminary separation of spectral components during the data acquisition phase rather than requiring complex post-acquisition modeling. By measuring the illumination spectrum separately and subtracting it from the sample spectrum during or immediately after acquisition, the method eliminates irrelevant components (illumination and background) before final analysis. This preliminary action simplifies subsequent material identification while maintaining clarity of intrinsic spectral features.
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 acquisition of a consistent and complete intrinsic spectral signature, enhancing signal intensity and clarity by removing noise and irrelevant components, thereby improving the accuracy of material identification and characterization across the electromagnetic spectrum.
Implementation Method 1
The basic principle of intrinsic spectroscopy is that intrinsic spectral components of a material of interest can only be generated when the material of interest absorbs energy.
Implementation Method 2
Once the sample material is illuminated with the corresponding illumination source it will absorb some of that illumination energy as represented by the negative area (C) and will also emit or reflect some of that illumination energy as illustrated by the area under the curve (D).
Data Source
AI summary
A method is provided to obtain a full range intrinsic spectral signature for spectroscopy and spectral imaging. The method eliminates the irrelevant spectral components and is used to normalize the spectral intensities across the full wavelength ranges obtained from different instrumentation. The method determines the intrinsic instrument noise levels and the noise level across the spectral range is averaged for each spectrum. By determining the percent of the integrated instrument noise relative to the integrated illumination energy for each instrument, the instrument noise can be normalized to one common value and the intensity values of the intrinsic sample spectra can be normalized proportionately and combined into a continuous intrinsic spectrum across the wavelength ranges of the contributing instruments. The methodology is also implemented in spectral imaging and spectral data cubes.