Adaptive Temporal Noise Reduction Filter Design
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Solution Overview
Problem
Conventional noise reduction techniques for video images fail to adequately account for the temporal variance of noise, leading to varying perceived noise levels due to differing temporal characteristics, which are influenced by image capture conditions such as ISO sensitivity and temperature, resulting in suboptimal noise reduction when motion and image processing are similar but noise characteristics differ.
Innovation Solution
A noise reduction apparatus and method that acquire noise characteristics and video image characteristics, reflect human visual sensitivity, and design filters to suppress noise components in frequency bands easily perceived by the human eye, using a Wiener filter to improve the signal-to-noise ratio and adapt noise reduction processing to specific temporal noise characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional temporal filter-type noise reduction is applied, then noise can be reduced while maintaining resolution, but the temporal variance of noise is not adequately addressed, leading to suboptimal noise reduction when noise characteristics differ
Solution Approach 1:
The patent implements dynamic adaptation of noise reduction processing by detecting temporal noise characteristics and switching between different processing modes. The system dynamically adjusts the noise reduction algorithm based on real-time noise variance detection, enabling it to adapt to varying noise conditions while maintaining optimal noise reduction effectiveness.
Solution Approach 2:
The patent changes processing parameters based on detected noise characteristics. When high temporal noise variance is detected, the system switches to a noise reduction mode that accounts for temporal variations, whereas low variance conditions use standard temporal filtering. This parameter adaptation resolves the contradiction by making the system versatile to different noise conditions while maintaining precision in each specific condition.
2Adaptability or versatility
If noise reduction processing is switched based on object motion or upstream image processing, then adaptive noise reduction is achieved, but temporal characteristics of noise itself are not considered, resulting in insufficient noise suppression
Solution Approach 1:
The patent introduces feedback mechanisms where the system detects temporal noise characteristics from the video signal and uses this information to adjust the noise reduction processing. The noise variance detection unit continuously monitors noise properties and feeds this information back to the noise reduction unit, which then adapts its processing accordingly. This closed-loop feedback ensures both adaptability to different conditions and precision in noise suppression.
Solution Approach 2:
The patent performs preliminary detection of temporal noise characteristics before applying noise reduction processing. By detecting noise variance in advance and determining appropriate processing modes beforehand, the system ensures that the correct noise reduction strategy is applied, achieving both adaptability and effectiveness without trial-and-error adjustments.
3Device complexity
If standard temporal filtering is used, then processing simplicity is maintained, but noise components in frequency bands easily perceived by human eye are not effectively suppressed
Solution Approach 1:
The patent segments the noise reduction processing into multiple stages: temporal noise characteristic detection, noise variance analysis, processing mode determination, and conditional noise reduction application. This segmentation allows the system to maintain simplicity in each individual stage while achieving effective suppression of perceptible noise through the coordinated operation of all stages.
Solution Approach 2:
The patent applies noise reduction processing selectively rather than uniformly. By detecting temporal noise characteristics and applying enhanced noise reduction only when and where needed (when high variance is detected), the system avoids the complexity of always applying full noise reduction while ensuring that perceptible noise is effectively suppressed in critical cases.
Data Source
AI summary
A noise reduction apparatus includes an input unit to input a captured image signal from a capturing unit. An acquisition unit acquires, according to a user operation, a temporal noise signal of the capturing unit based on the captured image signal. An estimation unit estimates an ideal image signal that has no noise, based on the captured image signal and the temporal noise signal. A removing unit removes a temporal frequency component higher than a predetermined threshold from each of the estimated ideal image signal and the acquired temporal noise signal. A generating unit generates a filter used for temporal noise reduction for a captured image signal in accordance with an added signal obtained by adding the ideal image signal from which the temporal frequency component has been removed by the removing unit and the noise signal from which the temporal frequency component has been removed by the removing unit.