Underwater exploration, inspection, and marine research increasingly depend on underwater drones equipped with high-resolution RGB-D cameras. However, in deep or turbid waters, light absorption and scattering cause significant color distortion—reds and yellows disappear first—reducing visibility for human operators and degrading the performance of computer vision algorithms used for object detection, mapping, and analysis. Traditional image enhancement methods often fail to account for depth-based color loss and struggle to perform in real time during fast-moving underwater operations.
AI and multimodal sensor fusion advances now enable real-time, depth-aware color correction. Combining RGB-D cameras with deep learning, these models allow subaquatic drones to produce visually clear and scientifically reliable footage in turbid or deep waters.
Conceptual Design
AI underwater color correction: Bringing true colors back to the deep
Fluendo’s approach directly integrates a depth-aware AI model into the underwater drone’s onboard video processing pipeline. By utilizing RGB images and depth maps from the RGB-D camera, the system restores the original color spectrum distorted by underwater absorption and scattering..
Our AI models are trained on a wide range of simulated and real underwater datasets, enabling precise estimation of color values based on pixel depth, ambient lighting conditions, and water type. This ensures that reds, yellows, and other wavelengths diminished at depth are accurately reconstructed.
The system delivers real-time, color-corrected video for both live pilot feedback and marine researchers, while also enhancing the performance of downstream computer vision tasks such as object detection, mapping, and inspection in challenging underwater environments.
Conceptual Design
AI underwater color correction: Bringing true colors back to the deep
Fluendo’s approach directly integrates a depth-aware AI model into the underwater drone’s onboard video processing pipeline. By utilizing RGB images and depth maps from the RGB-D camera, the system restores the original color spectrum distorted by underwater absorption and scattering..
Our AI models are trained on a wide range of simulated and real underwater datasets, enabling precise estimation of color values based on pixel depth, ambient lighting conditions, and water type. This ensures that reds, yellows, and other wavelengths diminished at depth are accurately reconstructed.
The system delivers real-time, color-corrected video for both live pilot feedback and marine researchers, while also enhancing the performance of downstream computer vision tasks such as object detection, mapping, and inspection in challenging underwater environments.
The value we deliver: How we boost your business
AI Performance for Accurate Detection
Depth-aware color correction improves AI accuracy, ensuring better object detection and classification for more reliable underwater data.
Edge Monitoring for Real-Time Flexibility
The system processes data directly on the drone, enabling low-latency, real-time operations with flexible adaptability for various missions.
Restored Visual Clarity for Enhanced Visibility
AI-driven color correction restores true color, enhancing visibility for both real-time operations and post-mission analysis.
Cost-effective sensor integration
Depth-aware AI on an RGB-D camera can reduce the need for expensive radar or sonar systems. This lowers equipment costs, simplifies the drone’s design, and improves power efficiency.
AI Performance for Accurate Detection
Depth-aware color correction improves AI accuracy, ensuring better object detection and classification for more reliable underwater data.
Edge Monitoring for Real-Time Flexibility
The system processes data directly on the drone, enabling low-latency, real-time operations with flexible adaptability for various missions.
Restored Visual Clarity for Enhanced Visibility
AI-driven color correction restores true color, enhancing visibility for both real-time operations and post-mission analysis.
Cost-effective sensor integration
Depth-aware AI on an RGB-D camera can reduce the need for expensive radar or sonar systems. This lowers equipment costs, simplifies the drone’s design, and improves power efficiency.