Charged-particle Microscope Image Quality Enhancement via Height-Guided Partitioning
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Solution Overview
Problem
Conventional charged-particle microscopes face difficulties in achieving high image quality for complex pattern areas, such as lower layer patterns and hole bottoms, due to limitations in hardware improvements and existing image processing methods, which fail to enhance contrast, signal-to-noise ratio, and resolution without deteriorating the overall image quality.
Innovation Solution
A method and device that utilize area partitioning and image processing based on height information from design data to calculate definition enhancement intensity for each local area, allowing for targeted image quality improvement without compromising the overall image quality, and enabling user input for specific enhancement needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hardware such as charged-particle optical system and detection system is improved to detect larger amount of charged particles from lower layer patterns and hole bottoms, then detection capability is improved, but device complexity increases and dramatic improvement is difficult
Solution Approach 1:
The patent replaces hardware improvements with software-based image processing methods. By using image processing techniques to enhance the visibility of lower layer patterns and hole bottoms, the invention achieves detection improvement without modifying the complex charged-particle optical system or detection hardware.
2Measurement precision
If conventional image processing methods are applied to enhance image quality, then overall image processing is performed, but image quality of specific difficult areas (lower layer patterns, hole bottoms) deteriorates or cannot be improved without affecting entire image
Solution Approach 1:
The patent applies local contrast correction that operates on specific local areas (lower layer patterns, hole bottoms) independently. By dividing the image into multiple local areas and applying appropriate correction to each, the invention improves image quality in difficult areas without compromising the overall image quality.
Solution Approach 2:
The patent segments the image into multiple local areas based on height information from design data. This segmentation allows different image processing parameters to be applied to different regions, enabling targeted improvement of specific areas while maintaining overall image quality.
3Measurement precision
If conventional image processing uses only captured image or image capturing conditions, then processing simplicity is maintained, but sufficient image quality improvement performance cannot be achieved for complex patterns
Solution Approach 1:
The patent incorporates height information from design data as preliminary information before performing image processing. By using this pre-acquired information to guide the image processing, the invention achieves better performance for complex patterns without adding significant processing complexity during the actual imaging phase.
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
The method effectively enhances image quality for challenging areas like lower layer patterns and hole bottoms, improving visibility and resolution while maintaining the integrity of the entire image, allowing for accurate defect detection and pattern measurement.
Implementation Method 1
A charged-particle microscope acquires a magnified image of a sample as the object by irradiating the sample with a charged particle beam and detecting particles (charged particles (of a type identical with or different from the irradiating charged particles), electromagnetic waves or photons) emitted from or passing through the sample.
Data Source
AI summary
A high-performance image quality improvement process, capable of improving the image quality of low-definition areas (lower layer patterns in a multilayer, bottoms of holes in a hole pattern, etc.), is performed to a captured image. Definition enhancement intensity is calculated using height information included in design data or estimate values of sample height information calculated from the captured image, and the image quality improvement process is performed to the captured image using the definition enhancement intensity.