Super-Resolution Microscopy Least Squares Noise Demodulation
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Solution Overview
Problem
Existing image forming methods in microscopy face challenges in achieving high resolution while minimizing noise, particularly in samples with thickness or height, where noise components become significant, leading to erroneous image demodulation and potential sample damage from increased light intensity.
Innovation Solution
The method involves modulating the phase of illuminating light using a diffraction grating with a narrow period, acquiring multiple images with varying modulation phases, and applying the method of least squares to suppress noise and enhance spatial frequency components, allowing for high-resolution image formation without excessive light intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If linear calculation demodulation is applied to picked-up images, then high-resolution images can be obtained, but noise components cause erroneous image demodulation
Solution Approach 1:
The patent extracts and separates noise components from the picked-up images through statistical analysis. By identifying and removing dark current noise, thermal noise, and shot noise components, the method isolates the true signal from noise contamination, enabling accurate demodulation of high-resolution images without erroneous effects from noise components.
Solution Approach 2:
The patent implements feedback by using the statistical properties of noise to correct the demodulation process. The system analyzes noise characteristics from multiple picked-up images and uses this information to adjust and refine the demodulation calculations, ensuring that noise components do not cause erroneous results in the final high-resolution image.
2Illumination intensity
If light source intensity is increased to reduce noise impact, then brighter images are obtained, but sample damage occurs
Solution Approach 1:
The patent converts the harmful effect of noise into a beneficial process by using noise statistical properties as a tool for image improvement. Instead of treating noise purely as a detrimental factor requiring higher light intensity, the method analyzes noise characteristics and uses this information to enhance image quality through statistical processing, thereby achieving bright, high-quality images without increasing light source intensity and causing sample damage.
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 effectively reduces noise components and achieves high-resolution images by accurately determining the optical transfer function, enabling improved microscopic observation without sample damage from excessive light.
Implementation Method 1
an optical microscope with a high resolution is constructed in which a sample image is spatially modulated by a diffraction grating placed in the vicinity of the object of observation
Data Source
Figure 1
AI summary
More images than the spatially modulated components of the illuminating light are acquired, and signal components are determined by applying the method of least squares to the plurality of picked-up images. In this way, high-resolution images with a lowered noise component can be obtained in a super-resolution microscope in which the sample is illuminated using spatially modulated illuminating light, the applied spatial modulation is demodulated by subjecting the acquired images to calculation processing, and high-resolution sample images are thus obtained.