Image Processing Apparatus Noise Reduction via Phase Variance
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Solution Overview
Problem
Existing image processing technologies adjust both meaningful subtle motion changes and random noise, leading to deteriorated image quality due to the adjustment of random noise in moving images.
Innovation Solution
An image processing apparatus that includes a change detection unit to identify direction changes orthogonal to image edges and a reliability estimation unit to differentiate between noise-induced and meaningful changes, allowing for selective adjustment of phase changes based on variance values, thereby reducing random noise adjustment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If an image processing apparatus adjusts the amount of change in subtle motion change of a moving image, then the visualization of physical phenomena and removal of unnecessary image fluctuations is improved, but random noise mixed in the moving image is also adjusted leading to deteriorated image quality
Solution Approach 1:
The patent segments the adjustment process by separating meaningful subtle motion changes from random noise through reliability estimation. The change detection unit divides the image into edge components and non-edge components, and the reliability estimation unit further segments adjustments based on variance values, applying different adjustment levels to different regions and types of changes.
Solution Approach 2:
The patent implements local quality by applying selective adjustment based on reliability values. High-reliability regions (with low variance) receive full adjustment while low-reliability regions (with high variance) receive reduced or no adjustment. This localized differential adjustment preserves image quality in noise-prone areas while maintaining motion enhancement in reliable areas.
2Measurement precision
If temporal filter is applied to detect subtle motion change based on phase change, then detection precision is improved, but random noise detection is also enhanced leading to over-adjustment
Solution Approach 1:
The reliability estimation unit acts as an intermediary between the change detection unit and the adjustment unit. It introduces a reliability value (based on variance) that mediates the adjustment process, allowing the system to distinguish between genuine subtle motion changes and random noise before applying adjustment, thus preventing over-adjustment of noise.
Solution Approach 2:
The patent implements feedback through the reliability estimation mechanism. The variance value calculated from temporal fluctuations provides feedback about the reliability of detected changes, which then feeds back to control the adjustment strength. This closed-loop approach ensures that adjustment is proportional to the confidence in the detected change.
Data Source
AI summary
An image processing apparatus includes a change detection unit configured to detect a direction change, which is a temporal fluctuation in a plausible direction orthogonal to an edge determined for each pixel in an edge image indicating a high frequency component in an image that is an image processing target, and a phase change, which is a temporal fluctuation of a phase of the high frequency component according to the direction change, and a reliability estimation unit configured to estimate reliability indicating that the detected phase change is not a change caused by noise based on a variance value of the direction change per unit time.