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Dark channel prior based video dehazing algorithm with sky preservation and its embedded system realization for ADAS
Optics Express
|May 5, 2019
Summary
This study enhances the Dark Channel Prior (DCP) dehazing method by reducing computational complexity and improving sky region processing. The optimized algorithm offers stable, real-time video dehazing for applications like surveillance.
Area of Science:
- Computer Vision
- Image Processing
Background:
- Dark Channel Prior (DCP) is a key image dehazing technique.
- DCP suffers from high computational cost, sky over-enhancement, and flickering artifacts.
Purpose of the Study:
- To address the limitations of the Dark Channel Prior (DCP) dehazing method.
- To improve real-time video processing for dehazing applications.
Main Methods:
- Implemented fast 1D filters, look-up tables, and program optimization to reduce complexity.
- Utilized guided filter for sky detection and noise preservation.
- Introduced an airlight update strategy and adjusted guided filter radius to minimize flickering.
- Developed a novel airlight estimation method for enhanced dehazing.
Main Results:
- Achieved significant reduction in computational complexity.
- Successfully preserved sky regions, avoiding over-enhancement.
- Reduced flickering artifacts in video sequences.
- Demonstrated stable and improved dehazing results.
Conclusions:
- The proposed enhanced DCP algorithm provides stable, real-time dehazing.
- The method is suitable for Advanced Driver-Assistance Systems (ADAS), surveillance, and monitoring.
- Achieved processing speeds of 75 fps and 23 fps on embedded platforms.
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