The ocean covers about 71% of the earth's surface which contains an enormous amount of life and organic and inorganic resources. But, with minimal knowledge about the marine environment and deep-sea world, the techniques for marine environment observation and exploration are still very limited. For instance, marine ecological mutilations through natural and anthropogenic activities are occurring at a high rate recently, which requires rapid observation and mitigation systems. Consequently, the necessity for marine observation is pushing the scientific horizons on multiple fronts.
Meanwhile, it should be noted that optics and machine vision has been developing very fast in recent years. A lot of novel technology, methods, devices and systems have been transferred from in-land to marine applications, e.g., novel optical sensors for in situ underwater measurements, automated and intelligent machine vision systems for in situ underwater measurement, object identification and time-series analysis, which provides powerful tool and support for the development of marine science.
The aim of this Research Topic is to promote new insights into marine environment observation. The topic especially focuses on optics and machine vision technology, methods, device or systems for marine observation, using individual or interdisciplinary approaches. Marine observation and sampling through innovative underwater robotics systems are also welcome in the topic.
This topic encourages authors from the fields of optics, machine vision, machine learning, marine science, etc., to submit original research articles and review articles, to discuss both the development and challenges of optics and machine vision for marine observation.
We are seeking contribution for this topic on the following subjects:
－ Optical sensors and machine vision for marine observation
－ Optical imaging in turbid environment
－ Image recovery and restoration
－ Image processing
－ Applications of machine learning in marine observation
－ Adequate monitoring and sampling systems
－ Underwater 3D modelling
－ Underwater object identification
－ Data analysis based on optical measurement or vision systems
The ocean covers about 71% of the earth's surface which contains an enormous amount of life and organic and inorganic resources. But, with minimal knowledge about the marine environment and deep-sea world, the techniques for marine environment observation and exploration are still very limited. For instance, marine ecological mutilations through natural and anthropogenic activities are occurring at a high rate recently, which requires rapid observation and mitigation systems. Consequently, the necessity for marine observation is pushing the scientific horizons on multiple fronts.
Meanwhile, it should be noted that optics and machine vision has been developing very fast in recent years. A lot of novel technology, methods, devices and systems have been transferred from in-land to marine applications, e.g., novel optical sensors for in situ underwater measurements, automated and intelligent machine vision systems for in situ underwater measurement, object identification and time-series analysis, which provides powerful tool and support for the development of marine science.
The aim of this Research Topic is to promote new insights into marine environment observation. The topic especially focuses on optics and machine vision technology, methods, device or systems for marine observation, using individual or interdisciplinary approaches. Marine observation and sampling through innovative underwater robotics systems are also welcome in the topic.
This topic encourages authors from the fields of optics, machine vision, machine learning, marine science, etc., to submit original research articles and review articles, to discuss both the development and challenges of optics and machine vision for marine observation.
We are seeking contribution for this topic on the following subjects:
－ Optical sensors and machine vision for marine observation
－ Optical imaging in turbid environment
－ Image recovery and restoration
－ Image processing
－ Applications of machine learning in marine observation
－ Adequate monitoring and sampling systems
－ Underwater 3D modelling
－ Underwater object identification
－ Data analysis based on optical measurement or vision systems