Image Processing Device Conditional Color Averaging Noise Reduction
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Solution Overview
Problem
Existing noise reduction methods for images struggle to effectively reduce color noise while maintaining contrast, especially when images of a single subject are acquired under different conditions with varying blurring levels or focal lengths.
Innovation Solution
An image processing device and method that includes a color space conversion unit to calculate brightness and color difference signals from RGB signals, a determination unit to assess differences between these signals, and an averaging unit to average color difference signals only when the absolute difference is below a threshold, thereby reducing noise while preserving contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If color difference signals are averaged from two images acquired under different image acquisition conditions, then color noise is reduced, but image contrast deteriorates
Solution Approach 1:
The patent applies local quality by performing conditional averaging only in regions where the absolute difference between color difference signals is below a threshold. This means different processing is applied to different regions of the image: regions with small color differences are averaged to reduce noise, while regions with large color differences are preserved to maintain contrast. The processing is localized to specific areas based on their individual characteristics rather than applying a uniform operation to the entire image.
2Productivity
If images with varying blurring levels are processed together, then processing efficiency is improved, but noise reduction effectiveness deteriorates
Solution Approach 1:
The patent uses parameter changes by comparing the absolute difference between color difference signals as a criterion to determine whether averaging should be performed. By changing the processing approach based on the measured parameter (color difference magnitude), the system can adaptively handle images with varying blurring levels. When the color difference is small, averaging is applied to reduce noise; when the color difference is large, averaging is avoided to preserve image details, thus maintaining noise reduction effectiveness across different image conditions.
3Device complexity
If color difference signals are averaged without threshold comparison, then processing simplicity is maintained, but image quality deteriorates
Solution Approach 1:
The patent applies segmentation by dividing the image processing into distinct stages: first comparing the absolute difference between color difference signals against a threshold, then conditionally averaging based on the comparison result. This segmented approach separates the decision-making process from the execution process, adding a quality control step that prevents inappropriate averaging while maintaining relatively simple processing logic through clear conditional branches.
Data Source
AI summary
An image processing device according to the present invention includes: a color space conversion unit that calculates brightness signals and color difference signals from RGB signals of two images of a single subject acquired under different image acquisition conditions; a color difference determination unit that determines whether or not the absolute value of the difference between the color difference signals of the two images calculated by the color space conversion unit is smaller than a predetermined threshold value; and a color averaging unit that, if the color difference determination unit determines that the absolute value of the difference between the color difference signals of the two images is smaller than the threshold value, averages the color difference signals of the two images and calculates average color difference signals.