Time-lapse Video Flicker Reduction via Luminance Curve Fitting
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Solution Overview
Problem
Time-lapse videos often suffer from exposure changes and flicker artifacts due to varying ambient conditions, which are exacerbated when images with different exposure parameters are played back at a higher frame rate, leading to undesirable brightness fluctuations.
Innovation Solution
Adaptive image processing techniques that involve calculating YCBCR values, curve-fitting average luminance values over consecutive frames, and adjusting pixel luminance to smooth out exposure transitions, thereby reducing flicker and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If images are captured at a lower frame rate for time-lapse video, then the duration of the captured event is compressed, but exposure changes and flicker artifacts occur when played back at higher frame rates
Solution Approach 1:
The system performs preliminary analysis of exposure parameters during the time-lapse capture phase, storing metadata about each frame's exposure settings. This preliminary action enables post-processing adjustments that compensate for exposure variations before the video is assembled and played back, preventing flicker artifacts from manifesting in the final output.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting exposure-related parameters (such as brightness, contrast, and gamma correction) during post-processing. By modifying these parameters based on analyzed exposure variations between frames, the system compensates for the inherent exposure inconsistencies that arise from capturing images at lower frame rates over extended periods.
2Illumination intensity
If auto-exposure adjusts exposure parameters between captured images to account for ambient light changes, then lighting conditions are adapted, but flicker artifacts are introduced when images are played back at higher frame rates
Solution Approach 1:
The system implements feedback by analyzing the exposure parameters of each captured frame and using this information to guide post-processing adjustments. By continuously monitoring exposure variations and applying compensatory adjustments during assembly, the system creates a feedback loop that eliminates flicker artifacts while preserving the beneficial exposure adaptations made during capture.
Solution Approach 2:
The patent applies dynamics by implementing a dynamic adjustment process that adapts to the specific exposure characteristics of each frame sequence. Rather than using fixed correction parameters, the system dynamically calculates and applies adjustments based on the actual exposure variations present in the captured images, enabling flexible compensation for different lighting conditions and capture scenarios.
3Adaptability or versatility
If images with significantly different exposure parameters are assembled into time-lapse video, then the full range of ambient conditions is captured, but jarring brightness transitions occur during playback
Solution Approach 1:
The system applies segmentation by dividing the time-lapse sequence into segments with similar exposure characteristics. By identifying and grouping frames with comparable exposure parameters, the system can apply targeted adjustments to each segment, ensuring smooth transitions between frames while preserving the full range of ambient conditions captured across the entire sequence.
Data Source
AI summary
Techniques and devices for post-processing time-lapse videos are described. The techniques include obtaining an input time-lapse sequence of frames and determining a visual metric value, e.g., average luminance, for each frame. A curve of best fit may then be determined for the visual metric values of the frames. The visual metric values, e.g., the average luminance values, of the plurality of frames may then be adjusted, e.g., by adjusting the visual metric values of each frame to be equal to the corresponding value determined by the curve of best fit. Some embodiments include further adjusting the visual metric values to be equal to a weighted average of the adjusted visual metric values for adjacent frames in the time-lapse sequence. Finally, a visual characteristic of the frames, e.g., an image histogram, may be adjusted based on the frame's determined adjusted visual metric value, and an output time-lapse sequence may be generated.