Radiographic Image Noise Reduction via Structure Determination
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Solution Overview
Problem
Existing radiographic image processing techniques face challenges in accurately estimating noise characteristics due to the influence of other image processing types, such as sharpening, dynamic range compression, and tone conversion, which can alter the relationship between radiation dose and noise, leading to inaccurate noise reduction.
Innovation Solution
An image processing apparatus that determines the structure present in target pixels of a radiographic image using a structure determination unit, allowing for separate and sequential image processing operations, including sharpening and noise reduction, to accurately assess noise characteristics and reduce noise without blurring structures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If other types of image processing (sharpening, dynamic range compression, tone conversion) are performed prior to noise reduction processing, then image quality and structure enhancement are improved, but noise characteristic estimation accuracy deteriorates
Solution Approach 1:
The image processing system is divided into separate processing chains: one for quality enhancement (sharpening, dynamic range compression, tone conversion) and another for noise reduction. The structure determination unit operates on the original image or intermediate results to estimate noise characteristics independently, while the noise reduction processing unit receives both the enhanced image and noise characteristic information to perform accurate noise reduction without being affected by the nonlinear transformations in the quality enhancement chain.
Solution Approach 2:
The structure determination unit performs noise characteristic estimation before the noise reduction processing is applied. By determining the noise characteristics from the original image or intermediate processing results prior to noise reduction, the system establishes accurate noise models that can guide the subsequent noise reduction processing, ensuring that noise reduction parameters are optimized based on actual noise characteristics rather than being distorted by subsequent processing steps.
2Adaptability or versatility
If noise reduction processing is performed after other types of image processing, then configuration flexibility is improved, but noise characteristic accuracy deteriorates
Solution Approach 1:
The system implements a feedback mechanism where the structure determination unit continuously monitors and estimates noise characteristics from the image data, and this noise characteristic information is fed back to the noise reduction processing unit. This feedback loop allows the noise reduction processing to adapt to the actual noise characteristics even when performed after other image processing operations, maintaining accuracy while preserving configuration flexibility.
Solution Approach 2:
The structure determination unit acts as an intermediary between the quality enhancement processing and the noise reduction processing. It analyzes the image data to determine noise characteristics and structure information, then provides this information as guidance to the noise reduction processing unit, enabling accurate noise reduction even when the processing sequence is flexible and noise reduction occurs after other processing steps.
3Manufacturing precision
If nonlinear processing is applied prior to noise reduction, then image enhancement is improved, but noise correction accuracy deteriorates
Solution Approach 1:
The structure determination unit performs noise characteristic estimation at an appropriate stage before noise reduction processing is applied. By determining noise characteristics from the original image or intermediate results prior to both nonlinear enhancement and noise reduction, the system establishes accurate baseline noise models that can guide the noise reduction processing even after nonlinear transformations, preventing the distortion of noise characteristics.
Solution Approach 2:
The processing system is segmented into independent analysis and processing components. The structure determination unit independently analyzes noise characteristics from the image data, while the noise reduction processing unit uses this independently determined information to perform noise reduction. This segmentation allows nonlinear enhancement processing to improve image quality without compromising the accuracy of noise characteristic determination, as the noise analysis is performed separately and independently.
Data Source
AI summary
In a case where noise reduction processing is performed on an image acquired by radiography, the noise reduction processing is prevented from being influenced by other image processing performed in advance. A structure determination unit determines a structure present in a target pixel of a preprocessed captured image. A first image processing unit performs a predetermined image processing based on a determination result of the structure present in the target pixel of the preprocessed captured image. A second image processing unit performs image processing different from the predetermined image processing on an image acquired through the predetermined image processing performed by the first image processing unit.