Image Processing Stabilizing Video Brightness Without Ghosting
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Solution Overview
Problem
Videos captured with high frame rates under fluctuating light sources exhibit significant brightness and color fluctuations, which are not effectively addressed by existing methods, especially when fast-moving objects are present, leading to ghost images.
Innovation Solution
An image processing method that includes brightness adjustment, offset compensation, and time domain filtering, with specific steps involving color channel averaging, offset calculation, and filtering schemes to stabilize frames and preserve moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If adjacent frames are superimposed and averaged to reduce brightness and color fluctuations, then the brightness stability is improved, but ghost images appear when fast-moving objects are present
Solution Approach 1:
The patent applies dynamics by making the filtering operation selective rather than uniform. It dynamically identifies moving objects through frame differencing and applies different processing: time domain filtering is applied only to stationary regions while moving objects are excluded from filtering. This dynamic approach resolves the contradiction by adapting the filtering behavior to the local motion characteristics of different image regions.
Solution Approach 2:
The patent implements local quality by applying different processing strategies to different regions of the image. Stationary regions undergo time domain filtering to reduce fluctuations, while moving object regions are preserved without filtering. This localized differentiation allows brightness stabilization in static areas without creating ghost images in dynamic areas.
2Stability of the object's composition
If time domain filtering is applied to all pixels to reduce brightness fluctuations, then the color consistency is improved, but moving objects become blurred or ghosted
Solution Approach 1:
The patent segments the image into moving and stationary regions through frame differencing. By calculating the absolute difference between current and previous frames and comparing against a threshold, it creates a mask that separates the image into distinct regions. This segmentation enables selective application of time domain filtering only to stationary regions, preserving color consistency there while maintaining image clarity in moving object regions.
Solution Approach 2:
The patent applies local quality by differentiating processing based on regional characteristics. Stationary regions receive time domain filtering for color consistency, while moving object regions are preserved without filtering to maintain sharpness. This localized processing strategy resolves the contradiction between color consistency and image clarity.
3Measurement precision
If frame rate is increased to capture fast-moving objects clearly, then the motion capture precision is improved, but brightness and color fluctuations become more pronounced
Solution Approach 1:
The patent extracts the problematic component (moving objects) from the overall image processing. By identifying moving regions through frame differencing and excluding them from time domain filtering, it separates the processing paths. This extraction allows high frame rate capture of moving objects without applying filtering that would cause fluctuations, while still stabilizing brightness in stationary regions.
Data Source
AI summary
An image processing method and device is provided. The method includes: performing brightness adjustment on each frame of image in a video; performing offset compensation on each frame of image after the brightness adjustment; and performing time domain filtering on each frame of image after the offset compensation.