Mapping Image Smoothing via Coefficient of Variation Analysis
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Solution Overview
Problem
Existing image processing methods for mapping images obtained by detecting signals from specimens require manual determination of smoothing conditions, which is time-consuming and prone to errors, leading to variations in image quality.
Innovation Solution
An image processing apparatus and method that automatically determine the degree of smoothing based on the difference between maximum and minimum signal intensity values, using calculations such as the coefficient of variation and filter sizes, to perform smoothing processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If smoothing processing is performed on a mapping image using fixed conditions (wavelet transform, moving average filter), then the S/N ratio is improved, but image quality deteriorates depending on the image and user burden increases
Solution Approach 1:
The system automatically determines the optimal smoothing condition by calculating the coefficient of variation from the mapping image data itself, without requiring user intervention. The processor computes statistical parameters (mean, standard deviation, coefficient of variation) and selects appropriate smoothing methods and conditions based on these calculated values, enabling the system to serve itself in determining processing parameters.
Solution Approach 2:
The system dynamically adjusts smoothing parameters based on the calculated coefficient of variation. When the coefficient of variation exceeds a threshold, stronger smoothing methods (wavelet transform, moving average filter) are applied; when it is below the threshold, minimal or no smoothing is applied. This parameter adaptation resolves the contradiction by matching the smoothing intensity to the actual image characteristics.
2Manufacturing precision
If the user manually determines the smoothing condition for each mapping image, then image quality can be optimized, but it takes much time and the user may fail to find the optimal condition
Solution Approach 1:
The patent replaces the manual mechanical process of user determination with an automated computational system. The processor calculates the coefficient of variation and automatically selects smoothing conditions based on predetermined thresholds, substituting human judgment and manual operation with algorithmic decision-making. This eliminates time loss while maintaining optimal image quality through objective, consistent criteria.
Solution Approach 2:
The system uses feedback from the calculated coefficient of variation to automatically adjust smoothing conditions. The processor continuously evaluates the image data, computes statistical parameters, and uses this feedback to determine the appropriate smoothing method and intensity, creating a closed-loop system that optimizes image quality without user intervention.
3Reliability
If smoothing processing is applied to improve S/N ratio, then signal quality improves, but variations in determination of smoothing condition occur depending on the user
Solution Approach 1:
The system changes from subjective user-determined parameters to objective, calculated parameters. The coefficient of variation is computed from the actual image data, providing an objective measure of signal quality that consistently drives smoothing condition selection. This eliminates variations between different users while maintaining reliable signal quality improvement.
Solution Approach 2:
The patent creates a universal smoothing determination system that works consistently across different mapping images and users. By using the coefficient of variation as a universal metric and predetermined thresholds as universal decision criteria, the system achieves consistent results regardless of who operates it or what specific image is being processed, eliminating user-dependent variations.
Data Source
AI summary
Provided is an image processing apparatus, which is configured to perform smoothing processing on a mapping image obtained by detecting a signal emitted from one of a plurality of analysis areas of a specimen. The image processing apparatus includes: a memory; and a processor configured to execute a program stored in the memory to perform: processing for calculating a difference between a maximum value and a minimum value of signal intensity data being intensity information on the signal of one of pixels within the mapping image, and determining a degree of smoothing to be used for the smoothing processing based on the difference; and processing for performing the smoothing processing based on the determined degree of smoothing.