Optical Tomography Spectral Compensation for Pseudo Signal Elimination
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Solution Overview
Problem
OCT systems face challenges in obtaining accurate tomographic images due to disturbances in the spectral shape and intensity of the measuring light, leading to errors and pseudo signals, especially in high-resolution, high-sensitivity, and high-speed applications.
Innovation Solution
An optical tomography method that divides light into measuring and reference beams, detects interference light, and uses spectral component measurement and Gaussian transformation to generate a compensating signal, which stabilizes the image formation by removing noise and ensuring a Gaussian waveform, even with fluctuations in the measuring light's spectral shape and intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If broad band light source is used to achieve high resolution, then measurement precision is improved, but spectral shape stability deteriorates
Solution Approach 1:
The patent applies parameter changes by transforming the spectral data through Fourier transform and applying window functions to compensate for spectral shape variations. This mathematical transformation converts the spectral domain information into a form where the measurement precision is maintained despite the inherent instability of broad band light sources.
Solution Approach 2:
The patent combines multiple signal processing techniques (Fourier transform, window function application, spectral normalization) to create a composite measurement approach. This composite method integrates various processing steps to simultaneously achieve high resolution from broad band sources while compensating for their spectral instability.
2Productivity
If high output power light source is used to achieve high speed and high sensitivity, then productivity is improved, but spectral shape stability deteriorates
Solution Approach 1:
The patent implements feedback by continuously monitoring the spectral shape and applying real-time compensation through signal processing. The system measures the actual spectral characteristics and uses this information to correct the measurements, ensuring high sensitivity and speed while maintaining accuracy despite spectral variations from high power sources.
Solution Approach 2:
The patent transforms the measurement parameters through Fourier transform and spectral normalization, converting the unstable spectral domain data into a stable depth domain representation. This parameter transformation allows high output power sources to be used for fast imaging while the mathematical processing compensates for spectral instabilities.
3Productivity
If spectral shape fluctuation occurs, then measurement precision deteriorates due to pseudo signal generation, but imaging speed can be maintained
Solution Approach 1:
The patent converts the harmful effect of spectral shape fluctuations into a manageable parameter by measuring and characterizing the actual spectral shape. Instead of treating spectral instability as pure noise, the system uses the measured spectral characteristics to create compensation functions that eliminate pseudo signals while preserving genuine measurement information.
Solution Approach 2:
The patent applies parameter changes by transforming spectral domain measurements into depth domain measurements through Fourier transform. This transformation, combined with window function application, converts spectral shape variations into a form where their impact is minimized and can be compensated, maintaining both speed and accuracy.
4Productivity
If intensity fluctuation of measuring light occurs, then measurement precision deteriorates due to detection errors, but imaging speed can be maintained
Solution Approach 1:
The patent transforms the measurement from the spectral domain to the depth domain using Fourier transform. This parameter transformation allows the system to maintain high imaging speed while the transformed data is less sensitive to intensity fluctuations. Additionally, spectral normalization compensates for intensity variations before transformation.
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 stable and accurate formation of tomographic images by eliminating pseudo signals and noise, ensuring high-quality imaging even with disturbances in the measuring light's spectral shape and intensity.
Implementation Method 1
interference light of the reflected light and reference light which have been superposed is detected
Implementation Method 2
the reflected light from the object and the reference light are superposed
Data Source
AI summary
Light emitted from a light source is divided into measuring light and reference light. The reflected light from the object and the reference light are superposed. Interference light of the reflected light and reference light which have been superposed is detected. Intensities of the reflected light in a plurality of positions in the direction of depth of the object are detected on the basis of the frequency and the intensity, and a tomographic image of the object is obtained on the basis of the intensity of the reflected light in each position in the direction of depth. A compensating signal is obtained by removing the spectral components of the measuring light from an interference signal obtained by detection of the interference light, and the compensating signal is provided for detection of the intensities of the reflected light after a Gaussian transform.