Edge-Enhancing Filter for Holographic Microscopy Detection
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Solution Overview
Problem
Conventional holographic microscopy methods for water quality monitoring are hindered by time-consuming calculations and the need for expensive, powerful computing equipment, making them unsuitable for small-size, low-cost sensor-level implementation in applications requiring rapid response times.
Innovation Solution
A method using edge-enhancing filters to process hologram data from a fluid sample, converting negative values to absolute, and detecting microscopic objects based on filtered hologram patterns, reducing computational power requirements and enabling faster detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional holographic microscopy methods are used for water quality monitoring, then detection capability is achieved, but computational complexity and cost increase significantly
Solution Approach 1:
The patent extracts only the essential features needed for detection by applying edge-enhancing filters that isolate the interference fringe patterns from the complete hologram. This selective extraction of critical information (edges and fringes) eliminates the need for processing the entire holographic dataset, thereby reducing computational complexity while preserving detection capability.
Solution Approach 2:
Instead of performing complete hologram reconstruction which requires full computational processing, the patent applies partial action by using edge-enhancing filters on selected portions of the hologram data. This partial processing approach focuses computational resources only on the regions and features that contain detection-relevant information, significantly reducing overall computational burden.
2Measurement precision
If conventional holographic microscopy methods are used for water quality monitoring, then detection capability is achieved, but response time increases due to time-consuming calculations
Solution Approach 1:
The patent extracts only the essential features needed for detection by applying edge-enhancing filters that isolate the interference fringe patterns from the complete hologram. This selective extraction of critical information (edges and fringes) eliminates the need for processing the entire holographic dataset, thereby reducing computational complexity while preserving detection capability.
Solution Approach 2:
The patent skips the time-consuming complete reconstruction phase of conventional holographic microscopy. By directly analyzing edge-enhanced features and interference fringes from the raw hologram data, the method rushes through the detection process using simplified computations, achieving rapid results without waiting for full reconstruction.
3Measurement precision
If conventional holographic microscopy methods are used for water quality monitoring, then detection capability is achieved, but equipment cost increases due to need for powerful computing equipment
Solution Approach 1:
The patent extracts only the essential features needed for detection by applying edge-enhancing filters that isolate the interference fringe patterns from the complete hologram. This selective extraction of critical information (edges and fringes) eliminates the need for processing the entire holographic dataset, thereby reducing computational complexity while preserving detection capability.
Solution Approach 2:
The patent replaces expensive, powerful computing equipment with simpler, more affordable computational approaches. By using edge-enhancing filters and focused feature analysis instead of complete hologram reconstruction, the method achieves detection capability using low-cost hardware that would be suitable for sensor-level implementation.
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 rapid and cost-effective detection of microscopic objects in fluids, facilitating the implementation of small-size, low-cost on-line monitoring systems for water quality and other applications.
Implementation Method 1
while illuminating the sample volume by coherent light, whereby the possible microscopic objects scatter part of the light
Implementation Method 2
the scattered and non-scattered light interfering so as to form interference fringes behind the microscopic objects
Data Source
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AI summary
A method (10) comprises: obtaining (101) prepared image data captured by an image sensor receiving light propagated across a sample volume, containing a fluid possibly comprising microscopic objects of foreign origin, while illuminating the sample volume by coherent light, the prepared image data comprising, for a microscopic object, a prepared hologram pattern with prepared spatially alternating intensity formed by the interference fringes; providing (102) filtered image data, comprising automatically filtering the prepared image data by an edge enhancing filter, the filtered image data comprising, for a prepared hologram pattern, a filtered hologram pattern; and automatically detecting (103), on the basis of the filtered hologram pattern, the presence of the microscopic object associated with the filtered hologram pattern in the sample volume of the fluid.