Super-Resolution Imaging via Angular Modulation and Pixel Extraction
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Solution Overview
Problem
Conventional optical microscopes are limited by the diffraction limit, making it difficult to distinguish adjacent details due to the fuzzy nature of light's diffraction pattern, requiring expensive equipment and complex data treatment for super-resolution imaging.
Innovation Solution
A method involving a digital camera with a matrix of sensors and a displacement block to capture and store pixel values in sub-diffraction limited distances, allowing for the construction of super-resolution images with simpler calculations and treatments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional optical microscopy is used, then the equipment cost is low and operation is simple, but the image resolution is limited by diffraction to approximately 150 nm
Solution Approach 1:
The patent divides the diffraction-limited image into multiple sub-images by capturing light from different angular directions using a spatial light modulator. Each sub-image contains partial information about the object, and these segmented sub-images are subsequently recombined through computational processing to reconstruct a super-resolution image that exceeds the diffraction limit.
Solution Approach 2:
The patent introduces an additional dimension by modulating the angular distribution of illumination light using a spatial light modulator. Instead of only capturing intensity information in the image plane, the system captures angular spectrum information by varying the illumination angles, thereby encoding spatial frequency information that would normally be inaccessible due to diffraction limitations.
2Measurement precision
If super-resolution techniques like STED or PALM are used, then image resolution exceeds the diffraction limit, but the equipment cost exceeds 1 M€ and complex post-signal data treatment is required
Solution Approach 1:
The patent replaces complex mechanical super-resolution systems (such as STED's depletion lasers or PALM's specialized fluorophores) with a computational approach using standard optical components. By using a spatial light modulator to encode angular information and applying computational algorithms to reconstruct the image, the system achieves super-resolution without requiring expensive specialized hardware or complex mechanical mechanisms.
Solution Approach 2:
The patent creates multiple virtual copies of the object by capturing images under different illumination angles. Each angle produces a slightly different diffraction pattern that contains complementary information. These copied views are then computationally integrated to reconstruct the super-resolution image, effectively synthesizing information that would be impossible to obtain from a single diffraction-limited image.
3Illumination intensity
If the illumination beam is focused to a diffraction-limited spot, then the light intensity is concentrated, but the resulting image cannot resolve details smaller than the diffraction limit
Solution Approach 1:
The patent dynamically varies the illumination angle using a spatial light modulator during the imaging process. By continuously changing the angular distribution of the focused light, the system captures multiple diffraction patterns from the same focused spot, each containing different spatial frequency information. This dynamic angular modulation allows the extraction of sub-diffraction details while maintaining the intensity concentration benefits of focused illumination.
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 production of high-resolution images comparable to other super-resolution techniques without the need for expensive equipment or complex data processing, improving image resolution across various magnifications.
Implementation Method 1
the resolution of an optical microscope is limited by light's diffraction. Indeed, because of light's diffraction, the image of a point is not a point, but appears as a fuzzy disk surrounded by a diffraction, called 'Airy disk' or 'point spread function'.
Implementation Method 2
an optical element for focusing the illumination beam on the support plate
Data Source
Figure 1~5
Figure 6~9
Figure 10~11
AI summary
Method for obtaining an super-resolution image (22) of an object (5), based upon an optical microscope (21) including a support plate (6) for bearing the object, an illumination source (1) for focusing an illumination beam (14) onto a target region of the support plate, a digital camera (9) including a matrix of sensors, comprising: capturing, by the digital camera, a first image of the target region; extracting, from the first image, a first block of pixel values provided by a sub-matrix (B0) of the matrix of sensors; displacing, by a sub-diffraction limited distance, the support plate by the displacement block along a displacement axis; capturing, by the digital camera, a second image of the target region; extracting, from the second image, a second block of pixel values provided by the sub-matrix (B0) of the matrix of sensors; storing said first and second blocks of pixel values as a first and second blocks of pixel values to be placed right next each other in the super-resolution image along the image axis (X, Y) corresponding to the displacement axis.