Video tonal stabilization via color states smoothing

Area of Science:

• Computer Vision
• Image Processing
• Video Stabilization

Background:

• Amateur videos often suffer from color tone jitter due to hand-held recording.
• Inconsistent exposure and white balance lead to undesirable tonal shifts.
• Existing methods may struggle with preserving natural video dynamics.

Purpose of the Study:

• To develop an effective method for removing video color tone jitter.
• To represent and analyze tonal variations using a novel 'color state' concept.
• To enhance the visual quality of amateur videos through tonal stabilization.

Main Methods:

• Introduced 'color state' to represent frame exposure and white balance.
• Computed color state by accumulating transformations between neighboring frames.
• Smoothed color state trajectories using L1 optimization and PCA dimensionality reduction.
• Developed a selective strategy to preserve extreme tonal changes and avoid artifacts.

Main Results:

• Demonstrated effective removal of video color tone jitter.
• Quantitative evaluations confirmed the method's superiority over previous techniques.
• Visual comparisons highlighted improved video quality and naturalness.
• The system proved effective as a preprocessing tool for other video editing tasks.

Conclusions:

• The proposed tonal stabilization method significantly reduces jitter in amateur videos.
• The selective strategy effectively balances jitter removal with the preservation of important tonal shifts.
• This technique offers a robust solution for improving video aesthetics and can be integrated into broader video processing pipelines.