Bridging the Gap Between Image Restoration and Navigational Safety in Hazy Conditions: A New Visibility Estimation Metric for Maritime Surveillance
arXiv:2606.30049v1 Announce Type: cross Abstract: Visibility distance is critical to maritime navigational safety because it determines the effective observation range of shipborne and shore-based monitoring systems. Under hazy conditions, degraded visual information shortens observable distance and increases navigational risks and economic losses. Although numerous image dehazing methods have been developed, conventional image quality assessment metrics, such as PSNR, SSIM, FSIM, FADE, and NIQE, cannot establish a physically interpretable relationship between restoration quality and practical
The increasing focus on autonomous navigation and persistent surveillance in maritime environments, particularly under challenging conditions, is driving innovation in AI-enhanced image restoration and objective visibility metrics.
Improved visibility estimation directly enhances maritime safety and operational efficiency, reducing risks and economic losses associated with poor visual conditions, which is critical for both commercial and naval applications.
The development of new, physically interpretable metrics for image restoration quality in hazy conditions will allow for more reliable deployment and evaluation of AI systems in real-world maritime surveillance, moving beyond subjective assessments.
- · Maritime logistics companies
- · Naval forces
- · AI/Computer Vision developers
- · Sensor manufacturers
- · Companies relying on outdated visibility assessment methods
Reduced incidents and accidents in maritime operations due to enhanced navigational awareness.
Accelerated adoption of autonomous vessels and AI-driven monitoring systems in challenging weather conditions.
Potential for new regulatory standards for AI-assisted maritime navigation based on these objective visibility metrics.
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Read at arXiv cs.LG