Video Dehazing Module Frame-by-Frame Haze Correction
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Solution Overview
Problem
Conventional methods for reducing haze in videos require manual determination of haze correction parameters on a single frame, leading to inconsistent results across different frames, causing visually jarring effects due to changing content.
Innovation Solution
A computer-implemented system automatically determines unique haze correction parameters for each video frame by analyzing dark channel, brightness, and atmospheric light characteristics, applying these parameters to generate a sequence of dehazed frames with smooth transitions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If manual haze correction parameters are determined on a single frame, then the processing complexity is reduced, but the consistency and quality of haze removal across all frames deteriorates
Solution Approach 1:
The system dynamically adjusts haze correction parameters for each video frame based on real-time analysis of dark channel, brightness, and atmospheric light characteristics. Unlike static single-frame correction, the parameters adapt to changing scene content, ensuring consistent haze removal quality across all frames while maintaining automated processing efficiency.
2Manufacturing precision
If unique haze correction parameters are determined for each video frame, then the haze removal consistency improves, but the processing complexity and computational requirements increase
Solution Approach 1:
The video processing is segmented into distinct analytical components: dark channel analysis, brightness assessment, and atmospheric light characterization. Each component processes specific features independently, allowing parallel computation and reducing overall processing complexity while maintaining frame-by-frame correction consistency.
Solution Approach 2:
The system changes key parameters (dark channel values, brightness levels, atmospheric light characteristics) for each frame to dynamically determine appropriate haze correction amounts. This parameter-based approach enables automated adaptation to varying scene conditions without requiring complex manual intervention for each frame.
3Speed
If single-frame haze correction parameters are applied to all frames, then the processing speed is maintained, but visual quality and natural appearance deteriorate due to jarring transitions
Solution Approach 1:
The system performs preliminary analysis of dark channel, brightness, and atmospheric light characteristics for each frame before applying haze correction. This preparatory step enables the determination of frame-specific correction parameters in advance, ensuring visual quality consistency while maintaining efficient processing throughput.
Data Source
AI summary
Computer-implemented systems and methods herein disclose automatic haze correction in a digital video. In one example, a video dehazing module identifies a scene including a set of video frames. The video dehazing module identifies the dark channel, brightness, and atmospheric light characteristics in the scene. For each video frame in the scene, the video dehazing module determines a unique haze correction amount parameter by taking into account the dark channel, brightness, and atmospheric light characteristics. The video dehazing module applies the unique haze correction amount parameters to each video frame and thereby generates a sequence of dehazed video frames.